Relevant bibliographies by topics / D Estimation

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'D Estimation'

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Published: 10 March 2023

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Journal articles on the topic "D Estimation"

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Li, Zhengzheng, Yan Zhang, and Scott E. Giangrande. "Rainfall-Rate Estimation Using Gaussian Mixture Parameter Estimator: Training and Validation." Journal of Atmospheric and Oceanic Technology 29, no. 5 (May 1, 2012): 731–44. http://dx.doi.org/10.1175/jtech-d-11-00122.1.

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Abstract This study develops a Gaussian mixture rainfall-rate estimator (GMRE) for polarimetric radar-based rainfall-rate estimation, following a general framework based on the Gaussian mixture model and Bayes least squares estimation for weather radar–based parameter estimations. The advantages of GMRE are 1) it is a minimum variance unbiased estimator; 2) it is a general estimator applicable to different rain regimes in different regions; and 3) it is flexible and may incorporate/exclude different polarimetric radar variables as inputs. This paper also discusses training the GMRE and the sensitivity of performance to mixture number. A large radar and surface gauge observation dataset collected in central Oklahoma during the multiyear Joint Polarization Experiment (JPOLE) field campaign is used to evaluate the GMRE approach. Results indicate that the GMRE approach can outperform existing polarimetric rainfall techniques optimized for this JPOLE dataset in terms of bias and root-mean-square error.
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Trömel, Silke, Matthew R. Kumjian, Alexander V. Ryzhkov, Clemens Simmer, and Malte Diederich. "Backscatter Differential Phase—Estimation and Variability." Journal of Applied Meteorology and Climatology 52, no. 11 (November 2013): 2529–48. http://dx.doi.org/10.1175/jamc-d-13-0124.1.

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AbstractOn the basis of simulations and observations made with polarimetric radars operating at X, C, and S bands, the backscatter differential phase δ has been explored; δ has been identified as an important polarimetric variable that should not be ignored in precipitation estimations that are based on specific differential phase KDP, especially at shorter radar wavelengths. Moreover, δ bears important information about the dominant size of raindrops and wet snowflakes in the melting layer. New methods for estimating δ in rain and in the melting layer are suggested. The method for estimating δ in rain is based on a modified version of the “ZPHI” algorithm and provides reasonably robust estimates of δ and KDP in pure rain except in regions where the total measured differential phase ΦDP behaves erratically, such as areas affected by nonuniform beam filling or low signal-to-noise ratio. The method for estimating δ in the melting layer results in reliable estimates of δ in stratiform precipitation and requires azimuthal averaging of radial profiles of ΦDP at high antenna elevations. Comparisons with large disdrometer datasets collected in Oklahoma and Germany confirm a strong interdependence between δ and differential reflectivity ZDR. Because δ is immune to attenuation, partial beam blockage, and radar miscalibration, the strong correlation between ZDR and δ is of interest for quantitative precipitation estimation: δ and ZDR are differently affected by the particle size distribution (PSD) and thus may complement each other for PSD moment estimation. Furthermore, the magnitude of δ can be utilized as an important calibration parameter for improving microphysical models of the melting layer.
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Xinhua Zhuang and Yan Huang. "Robust 3-D-3-D pose estimation." IEEE Transactions on Pattern Analysis and Machine Intelligence 16, no. 8 (1994): 818–24. http://dx.doi.org/10.1109/34.308478.

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Thành, Nguyễn Tường, Lê Văn Hùng, and Phạm Thành Công. "An Evaluation of Pose Estimation in Video of Traditional Martial Arts Presentation." Journal of Research and Development on Information and Communication Technology 2019, no. 2 (December 31, 2019): 114–26. http://dx.doi.org/10.32913/mic-ict-research.v2019.n2.864.

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Preserving, maintaining, and teaching traditional martial arts are very important activities in social life. That helps individuals preserve national culture, exercise, and practice self-defense. However, traditional martial arts have many differentposturesaswellasvariedmovementsofthebodyand body parts. The problem of estimating the actions of human body still has many challenges, such as accuracy, obscurity, and so forth. This paper begins with a review of several methods of 2-D human pose estimation on the RGB images, in which the methods of using the Convolutional Neural Network (CNN) models have outstanding advantages in terms of processing time and accuracy. In this work we built a small dataset and used CNN for estimating keypoints and joints of actions in traditional martial arts videos. Next we applied the measurements (length of joints, deviation angle of joints, and deviation of keypoints) for evaluating pose estimation in 2-D and 3-D spaces. The estimator was trained on the classic MSCOCO Keypoints Challenge dataset, the results were evaluated on a well-known dataset of Martial Arts, Dancing, and Sports dataset. The results were quantitatively evaluated and reported in this paper.
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Amorino, Chiara, and Eulalia Nualart. "Optimal convergence rates for the invariant density estimation of jump-diffusion processes." ESAIM: Probability and Statistics 26 (2022): 126–51. http://dx.doi.org/10.1051/ps/2022001.

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We aim at estimating the invariant density associated to a stochastic differential equation with jumps in low dimension, which is for d = 1 and d = 2. We consider a class of fully non-linear jump diffusion processes whose invariant density belongs to some Hölder space. Firstly, in dimension one, we show that the kernel density estimator achieves the convergence rate 1/T, which is the optimal rate in the absence of jumps. This improves the convergence rate obtained in Amorino and Gloter [J. Stat. Plann. Inference 213 (2021) 106–129], which depends on the Blumenthal-Getoor index for d = 1 and is equal to (logT)/T for d = 2. Secondly, when the jump and diffusion coefficients are constant and the jumps are finite, we show that is not possible to find an estimator with faster rates of estimation. Indeed, we get some lower bounds with the same rates {1/T, (logT)/T} in the mono and bi-dimensional cases, respectively. Finally, we obtain the asymptotic normality of the estimator in the one-dimensional case for the fully non-linear process.
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Xie, Jinhong, X. Michael Song, Marvin Sirbu, and Qiong Wang. "Kalman Filter Estimation of New Product Diffusion Models." Journal of Marketing Research 34, no. 3 (August 1997): 378–93. http://dx.doi.org/10.1177/002224379703400307.

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The authors introduce a new estimation procedure, Augmented Kalman Filter with Continuous State and Discrete Observations (AKF(C-D)), for estimating diffusion models. This method is directly applicable to differential diffusion models without imposing constraints on the model structure or the nature of the unknown parameters. It provides a systematic way to incorporate prior knowledge about the likely values of unknown parameters and updates the estimates when new data become available. The authors compare AKF(C-D) empirically with five other estimation procedures, demonstrating AKF(C-D)'s superior prediction performance. As an extension to the basic AKF(C-D) approach, they also develop a parallel-filters procedure for estimating diffusion models when there is uncertainty about diffusion model structure or prior distributions of the unknown parameters.
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Zhao, Xiaofeng, and Sixun Huang. "Estimation of Atmospheric Duct Structure Using Radar Sea Clutter." Journal of the Atmospheric Sciences 69, no. 9 (September 1, 2012): 2808–18. http://dx.doi.org/10.1175/jas-d-12-073.1.

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Abstract Retrieving atmospheric refractivity profiles from the sea surface backscattered radar clutter is known as the refractivity-from-clutter (RFC) technique. Because the relationship between refractivity and radar sea clutter is clearly nonlinear and ill posed, it is difficult to get analytical solutions according to current theories. Previous works treat this problem as a model parameter estimation issue and some optimization algorithms are selected to get approximate solutions. Two main factors that limit the accuracy of the estimation are that 1) the refractive environments are described by using some idealized refractivity parameter models that cannot describe the exact information of the refractivity profile, and 2) accurate modeling of the sea surface radar cross section (RCS) is very difficult. Rather than estimating a few model parameters, this paper puts forward possibilities of using the variational adjoint approach to jointly retrieve the every-height refractivity values and sea surface RCS using radar clutter data. The derivation of the adjoint model is accomplished by an analytical transformation of the parabolic equation (PE) in the continuous domain. Numerical simulations including range-independent and range-dependent RCS cases are presented to demonstrate the ability of this method for RFC estimations. Making use of the refractivity retrievals, propagation loss predictions are also presented.
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Chanwimaluang, T., Guoliang Fan, G. G. Yen, and S. R. Fransen. "3-D Retinal Curvature Estimation." IEEE Transactions on Information Technology in Biomedicine 13, no. 6 (November 2009): 997–1005. http://dx.doi.org/10.1109/titb.2009.2027014.

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Wilson, Greg, and H. Tuba Özkan-Haller. "Ensemble-Based Data Assimilation for Estimation of River Depths." Journal of Atmospheric and Oceanic Technology 29, no. 10 (October 1, 2012): 1558–68. http://dx.doi.org/10.1175/jtech-d-12-00014.1.

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Abstract A method is presented for estimating bathymetry in a river, based on observations of depth-averaged velocity during steady flow. The estimator minimizes a cost function that combines known information in the form of a prior estimate and measured data (including measurement noise). State augmentation is used to relate the measured variable (velocity) to the unknown parameter (bathymetry). Specifically, the unknown consists of deviations in depth about a known along-channel mean. Verification of the method is performed using a simple 1D channel geometry as well as for two real-world reaches. In all cases, the verification is based on nominal river depths of 3–10 m, channel widths of 50–100 m, and Froude numbers much less than one. Further tests are performed to assess the usefulness of various observation types and sampling schemes for this type of estimation.
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Hacking, Chris, Nitesh Poona, Nicola Manzan, and Carlos Poblete-Echeverría. "Investigating 2-D and 3-D Proximal Remote Sensing Techniques for Vineyard Yield Estimation." Sensors 19, no. 17 (August 22, 2019): 3652. http://dx.doi.org/10.3390/s19173652.

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Vineyard yield estimation provides the winegrower with insightful information regarding the expected yield, facilitating managerial decisions to achieve maximum quantity and quality and assisting the winery with logistics. The use of proximal remote sensing technology and techniques for yield estimation has produced limited success within viticulture. In this study, 2-D RGB and 3-D RGB-D (Kinect sensor) imagery were investigated for yield estimation in a vertical shoot positioned (VSP) vineyard. Three experiments were implemented, including two measurement levels and two canopy treatments. The RGB imagery (bunch- and plant-level) underwent image segmentation before the fruit area was estimated using a calibrated pixel area. RGB-D imagery captured at bunch-level (mesh) and plant-level (point cloud) was reconstructed for fruit volume estimation. The RGB and RGB-D measurements utilised cross-validation to determine fruit mass, which was subsequently used for yield estimation. Experiment one’s (laboratory conditions) bunch-level results achieved a high yield estimation agreement with RGB-D imagery (r2 = 0.950), which outperformed RGB imagery (r2 = 0.889). Both RGB and RGB-D performed similarly in experiment two (bunch-level), while RGB outperformed RGB-D in experiment three (plant-level). The RGB-D sensor (Kinect) is suited to ideal laboratory conditions, while the robust RGB methodology is suitable for both laboratory and in-situ yield estimation.
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Dissertations / Theses on the topic "D Estimation"

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Tewfik, Ahmed H. "Recursive estimation and spectral estimation for 2-D isotropic random fields." Thesis, Massachusetts Institute of Technology, 1987. http://hdl.handle.net/1721.1/14928.

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Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1987.
MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING
Bibliography: leaves 180-188.
by Ahmed Hossam Tewfik.
Sc.D.
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Kacete, Amine. "Unconstrained Gaze Estimation Using RGB-D Camera." Thesis, CentraleSupélec, 2016. http://www.theses.fr/2016SUPL0012/document.

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Dans ce travail, nous avons abordé le problème d’estimation automatique du regard dans des environnements utilisateur sans contraintes. Ce travail s’inscrit dans la vision par ordinateur appliquée à l’analyse automatique du comportement humain. Plusieurs solutions industrielles sont aujourd’hui commercialisées et donnent des estimations précises du regard. Certaines ont des spécifications matérielles très complexes (des caméras embarquées sur un casque ou sur des lunettes qui filment le mouvement des yeux) et présentent un niveau d’intrusivité important, ces solutions sont souvent non accessible au grand public. Cette thèse vise à produire un système d’estimation automatique du regard capable d’augmenter la liberté du mouvement de l’utilisateur par rapport à la caméra (mouvement de la tête, distance utilisateur-capteur), et de réduire la complexité du système en utilisant des capteurs relativement simples et accessibles au grand public. Dans ce travail, nous avons exploré plusieurs paradigmes utilisés par les systèmes d’estimation automatique du regard. Dans un premier temps, Nous avons mis au point deux systèmes basés sur deux approches classiques: le premier basé caractéristiques et le deuxième basé semi apparence. L’inconvénient majeur de ces paradigmes réside dans la conception des systèmes d'estimation du regard qui supposent une indépendance totale entre l'image d'apparence des yeux et la pose de la tête. Pour corriger cette limitation, Nous avons convergé vers un nouveau paradigme qui unifie les deux blocs précédents en construisant un espace regard global, nous avons exploré deux directions en utilisant des données réelles et synthétiques respectivement
In this thesis, we tackled the automatic gaze estimation problem in unconstrained user environments. This work takes place in the computer vision research field applied to the perception of humans and their behaviors. Many existing industrial solutions are commercialized and provide an acceptable accuracy in gaze estimation. These solutions often use a complex hardware such as range of infrared cameras (embedded on a head mounted or in a remote system) making them intrusive, very constrained by the user's environment and inappropriate for a large scale public use. We focus on estimating gaze using cheap low-resolution and non-intrusive devices like the Kinect sensor. We develop new methods to address some challenging conditions such as head pose changes, illumination conditions and user-sensor large distance. In this work we investigated different gaze estimation paradigms. We first developed two automatic gaze estimation systems following two classical approaches: feature and semi appearance-based approaches. The major limitation of such paradigms lies in their way of designing gaze systems which assume a total independence between eye appearance and head pose blocks. To overcome this limitation, we converged to a novel paradigm which aims at unifying the two previous components and building a global gaze manifold, we explored two global approaches across the experiments by using synthetic and real RGB-D gaze samples
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Müller, Werner, and Dale L. Zimmerman. "Optimal Design for Variogram Estimation." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1997. http://epub.wu.ac.at/756/1/document.pdf.

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The variogram plays a central role in the analysis of geostatistical data. A valid variogram model is selected and the parameters of that model are estimated before kriging (spatial prediction) is performed. These inference procedures are generally based upon examination of the empirical variogram, which consists of average squared differences of data taken at sites lagged the same distance apart in the same direction. The ability of the analyst to estimate variogram parameters efficiently is affected significantly by the sampling design, i.e., the spatial configuration of sites where measurements are taken. In this paper, we propose design criteria that, in contrast to some previously proposed criteria oriented towards kriging with a known variogram, emphasize the accurate estimation of the variogram. These criteria are modifications of design criteria that are popular in the context of (nonlinear) regression models. The two main distinguishing features of the present context are that the addition of a single site to the design produces as many new lags as there are existing sites and hence also produces that many new squared differences from which the variograrn is estimated. Secondly, those squared differences are generally correlated, which inhibits the use of many standard design methods that rest upon the assumption of uncorrelated errors. Several approaches to design construction which account for these features are described and illustrated with two examples. We compare their efficiency to simple random sampling and regular and space-filling designs and find considerable improvements. (author's abstract)
Series: Forschungsberichte / Institut für Statistik
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Vanhems, Anne. "Estimation non paramétrique de solutions d' équations différentielles." Toulouse 1, 2001. http://www.theses.fr/2001TOU10102.

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Notre travail a pour objet l' étude statistique de paramètres fonctionnels définis comme solutions d' équations différentielles dépendant de la loi de probabilité des données. De tels problèmes se posent fréquemment en économie, physique, finance où les modèles définissent les paramètres d' intérêt comme solutions d' équations différentielles
The objective of our work is to make statistical inference on functional parameters which are solutions of differential equations depending on the data distribution. Such problems are often encountered in economics, physics, finance, where the interest parameters are solutions of differential equations
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Oyini, Mbouna Ralph. "3-D Face Modeling from a 2-D Image with Shape and Head Pose Estimation." Diss., Temple University Libraries, 2014. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/305734.

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Electrical and Computer Engineering
Ph.D.
This paper presents 3-D face modeling with head pose and depth information estimated from a 2-D query face image. Many recent approaches to 3-D face modeling are based on a 3-D morphable model that separately encodes the shape and texture in a parameterized model. The model parameters are often obtained by applying statistical analysis to a set of scanned 3-D faces. Such approaches tend to depend on the number and quality of scanned 3-D faces, which are difficult to obtain and computationally intensive. To overcome the limitations of 3-D morphable models, several modeling techniques from 2-D images have been proposed. We propose a novel framework for depth estimation from a single 2-D image with an arbitrary pose. The proposed scheme uses a set of facial features in a query face image and a reference 3-D face model to estimate the head pose angles of the face. The depth information of the subject at each feature point is represented by the depth information of the reference 3-D face model multiplied by a vector of scale factors. We use the positions of a set of facial feature points on the query 2-D image to deform the reference face dense model into a person specific 3-D face by minimizing an objective function. The objective function is defined as the feature disparity between the facial features in the face image and the corresponding 3-D facial features on the rotated reference model projected onto 2-D space. The pose and depth parameters are iteratively refined until stopping criteria are reached. The proposed method requires only a face image of arbitrary pose for the reconstruction of the corresponding 3-D face dense model with texture. Experiment results with USF Human-ID and Pointing'04 databases show that the proposed approach is effective to estimate depth and head pose information with a single 2-D image.
Temple University--Theses
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Rose, Christopher James. "An adaptive D-STATCOM control scheme utilising impedance estimation." Thesis, University of Nottingham, 2016. http://eprints.nottingham.ac.uk/32915/.

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Concerns for energy security and the environment are driving significant changes in the way electrical power is generated and distributed. In many parts of the world, electrical power systems are gradually changing from centralised systems with a small number of large generators and substations performing most control operations to distributed systems, with a large number of devices providing control at a local level. Power electronic converters have an increasingly important role to play in modern electrical power systems. One example of power electronics in such systems is the STATCOM, a power electronic device which can be used to provide an efficient and effective means of controlling power system voltages. This thesis presents an investigation into STATCOM voltage control for distribution level power networks. In this work, a STATCOM voltage control structure is proposed and an impedance estimation algorithm is used to tune the controller gains in order to achieve the desired dynamic performance. This work demonstrates that the use of impedance estimation for controller tuning allows the STATCOM dynamics to remain consistent when installed on different systems or if the system impedance should change. In addition to proposing the voltage control structure, this thesis also proposes improvements to an earlier impedance estimation method, taking into account changes in converter structures and control methods since the method was first proposed.
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Azarbayejani, Ali J. "Nonlinear probabilistic estimation of 3-D geometry from images." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/29122.

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Yu, Xiaoju, and Hao Xin. "3-D Direction of Arrival Estimation with Two Antennas." International Foundation for Telemetering, 2011. http://hdl.handle.net/10150/595622.

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ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada
Inspired by human auditory system, an improved direction of arrival (DOA) technique using only two antennas with a scatterer in between them to achieve additional magnitude cues is proposed. By exploiting the incident-angle-dependent magnitude and phase differences between the two monopole antennas and applying 2-D / 3-D multiple signal classification algorithms (MUSIC), the DOA of an incident microwave signal can be estimated. Genetic algorithm is applied to optimize the scatterer geometry for the 3-D DOA estimation. The simulated results of both the azimuth and three-dimensional DOA estimation have shown an encouraging accuracy and sensitivity by incorporating a lossy scatterer.
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Marti, Lucas. "Estimation de la posture humaine par capteur RGB-D." Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30394.

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Dans le contexte du vieillissement de la population, le problème de la chute est un problème de santé publique. L'utilisation de la technologie est un axe important pour la prise en compte des enjeux liés à la chute. Nous voulons développer un système complet de détection et d'estimation de la chute à destination des maison de retraites et des particuliers dans un but d'amélioration de la prise en charge médicale et de limitation des conséquences de la chute. La solution de détection à l'aide d'un capteur ambiant déporté nous a semblé être la solution la plus adaptée. Les capteurs RGB-D (couleurs + profondeur) développés récemment sont un atout pour cela car ils sont peu chers, très commun et performants.La première partie de la thèse traite du problème de segmentation de la silhouette de la personne dans la scène observée. Nous présentons un algorithme qui fourni, grâce à une utilisation conjointe des images de couleurs et de profondeur, les silhouettes des différents personnes dans la pièce dans laquelle est situé le capteur. L'algorithme est robuste au changement de configuration de la pièce et notamment au déplacement d'objets. L'utilisation de caractéristiques propres à la profondeur nous permet d'atteindre des niveaux de performances suffisant pour une utilisation industrielle. Dans la seconde partie de la thèse nous abordons le problème de l'estimation de la posture humaine. Une fois les silhouettes segmentées grâce à l'algorithme de la première partie, nous voulons avoir les positions des articulations de la personne. Nous incrémentons sur les algorithmes déjà existants utilisant l'apprentissage et notamment les algorithmes des randoms forests en investiguant de nouvelles idées pour augmenter les performances. Nous déterminons les valeurs optimales de certains paramètres qui ne sont pas explorés dans les travaux précedents. Nous présentons un nouveau type de caractéristique à calculer sur les images de profondeur. Nous examinons enfin l'impact de l'équilibrage de la collection d'apprentissage dans notre contexte. L'algorithme fourni alors un ensemble de prédiction pour chaque articulation.Dans la troisième partie, nous traitons le problème du filtrage spatio-temporel des poses. Nous présentons différentes approches et nous intéressons à l'ambiguïté droite/gauche des membres et cherchons à traiter ce problème. Les approches utilisées se fonde sur le filtrage bayesien
In a world with an increasingly aging population, elderly people falling are a public health issue. The use of technology is a major development axis for fall management. We want to design a complete system for detection and estimation of falls. The target market for this system is medicalized retirement homes and individual homes. We want to improve the medical care of people after the fall in order to lower its consequences. A solution based on an ambient sensor seems to be the most adapted solution. Recent development in RGB-D (Color+Depth) sensing are a great asset thanks to their relatively low cost, wide availability and good performances. The first part of the thesis deals with the problem of segmenting people for the surrounding scene in our images. We present an algorithm that gives, thanks to use simultaneous use of color and depth, the silhouettes of each person in the room in which the sensor is installed. The algorithm is robust to the change of configuration of the room and especially to moving furniture. We use special consideration of depth to reach a performance level sufficient for an industrial application. The second part of the thesis deals with the estimation of the human posture. Once the silhouettes have been segmented with the algorithm of the first part, we want to get an estimation of every articulation of the person. We build on existing algorithms that use machine learning and in particular Random Forest by investigating new ideas to improve performances. We found optimal values for some parameters that were not previously investigated. We present a new feature to be computed on depth images. Finally we evaluate the impact of balancing the training database in our context. The algorithm provides a set of predictions for the position of every articulation. In the third part, we are interested in spatio-temporal filtering of the postures. We present different approaches and in particular we deal with the issue of left/right ambiguity that arises in the algorithm of the previous part. The approaches are based on Bayesian filtering
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Kaval, Huseyin. "2-d Mesh-based Motion Estimation And Video Object Manipulation." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/2/12608869/index.pdf.

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Motion estimation and compensation plays an important role in video processing applications. Two-dimensional block-based and mesh-based models are widely used in this area. A 2-D mesh-based model provides a better representation of complex real world motion than a block-based model. Mesh-based motion estimation algorithms are employed in both frame-based and object-based video compression and coding. A hierarchical mesh-based algorithm is applied to improve the motion field generated by a single-layer algorithm. 2-D mesh-based models also enable the manipulation of video objects which is included in the MPEG-4 standard. A video object in a video clip can be replaced by another object by the use of a dynamic mesh structure. In this thesis, a comparative analysis of 2-D block-based and mesh-based motion estimation algorithms in both frame-based and object-based video representations is performed. The experimental results indicate that a mesh-based algorithm produces better motion compensation results than a block-based algorithm. Moreover, a two-layer mesh-based algorithm shows improvement over a one-layer mesh-based algorithm. The application of mesh-based motion estimation and compensation to video object replacement and animation is also performed.
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Books on the topic "D Estimation"

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Basu, D. Statistical information and likelihood: A collection of critical essays by Dr. D. Basu. Edited by Ghosh J. K. Berlin: Springer-Verlag, 1988.

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Favaro, Paolo. 3-D shape estimation and image restoration: Exploiting defocus and motion blur. London: Springer, 2007.

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Great Britain. Department of the Environment., Binnie & Partners Consulting Engineers., and Foundation for Water Research, eds. Estimation of flood damage following potential dam failure: Guidelines, FR/D 0003, March 1991. Marlow, Buckinghamshire: Foundation for Water Research, 1991.

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Eremic, John C. Iterative methods for estimation of 2-D AR parameters using a data-adaptive Toeplitz approximation algorithm. Monterey, Calif: Naval Postgraduate School, 1991.

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Nadiri, M. Ishaq. Estimation of the depreciation rate of physical and R&D capital in the U.S. total manufacturing sector. Cambridge, MA: National Bureau of Economic Research, 1993.

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Irwin, Douglas A. High tech R&D subsidies: Estimating the effects of Sematech. Cambridge, MA: National Bureau of Economic Research, 1994.

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3-D Shape Estimation and Image Restoration. London: Springer London, 2007. http://dx.doi.org/10.1007/978-1-84628-688-9.

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Soatto, Stefano, and Paolo Favaro. 3-D Shape Estimation and Image Restoration. Springer, 2008.

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El-Shaer, Hamdy Taha M. Multichannel 2-D power spectral estimation and applications. 1987.

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Statistical Information and Likelihood: A Collection of Critical Essays by Dr. D. Basu. Springer, 2011.

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Book chapters on the topic "D Estimation"

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Cowburn, David, John Glushka, Frank DiGennaro, and Carlos B. Rios. "Parametric Estimation in 1-D, 2-D, and 3-D NMR." In Computational Aspects of the Study of Biological Macromolecules by Nuclear Magnetic Resonance Spectroscopy, 27–38. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4757-9794-7_2.

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Ma, Yi, Stefano Soatto, Jana Košecká, and S. Shankar Sastry. "Estimation of Multiple Motions from Two Views." In An Invitation to 3-D Vision, 228–60. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-0-387-21779-6_7.

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Schaffert, Roman, Markus Weiß, Jian Wang, Anja Borsdorf, and Andreas Maier. "Learning-Based Correspondence Estimation for 2-D/3-D Registration." In Informatik aktuell, 222–28. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-29267-6_50.

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Sahin, Caner, Guillermo Garcia-Hernando, Juil Sock, and Tae-Kyun Kim. "Instance- and Category-Level 6D Object Pose Estimation." In RGB-D Image Analysis and Processing, 243–65. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28603-3_11.

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Ge, Liuhao, Junsong Yuan, and Nadia Magnenat Thalmann. "Real-Time Hand Pose Estimation Using Depth Camera." In RGB-D Image Analysis and Processing, 355–76. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28603-3_16.

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Chen, Yang-Sheng, Yu-Chun Chen, Peng-Yuan Kao, Sheng-Wen Shih, and Yi-Ping Hung. "Estimation of 3-D Foot Parameters Using Hand-Held RGB-D Camera." In Computer Vision - ACCV 2014 Workshops, 407–18. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16634-6_30.

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Pan, Yingjie, Hong Zhu, and Ruirui Ji. "3-D Head Pose Estimation for Monocular Image." In Fuzzy Systems and Knowledge Discovery, 293–301. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11540007_35.

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Tang, Qirong, Xue Hu, Zhugang Chu, and Shun Wu. "6D Gripper Pose Estimation from RGB-D Image." In Lecture Notes in Computer Science, 120–25. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34995-0_11.

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Atapour-Abarghouei, Amir, and Toby P. Breckon. "Dealing with Missing Depth: Recent Advances in Depth Image Completion and Estimation." In RGB-D Image Analysis and Processing, 15–50. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28603-3_2.

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Otterbach, R. "Robust 3-D object recognition and pose estimation using 2-D image sequences." In Informatik aktuell, 295–302. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-79980-8_35.

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Conference papers on the topic "D Estimation"

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Liu, Chenchen, Yongzhi Li, Kangqi Ma, Duo Zhang, Peijun Bao, and Yadong Mu. "Learning 3-D Human Pose Estimation from Catadioptric Videos." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/118.

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Abstract:
3-D human pose estimation is a crucial step for understanding human actions. However, reliably capturing precise 3-D position of human joints is non-trivial and tedious. Current models often suffer from the scarcity of high-quality 3-D annotated training data. In this work, we explore a novel way of obtaining gigantic 3-D human pose data without manual annotations. In catedioptric videos (\emph{e.g.}, people dance before a mirror), the camera records both the original and mirrored human poses, which provides cues for estimating 3-D positions of human joints. Following this idea, we crawl a large-scale Dance-before-Mirror (DBM) video dataset, which is about 24 times larger than existing Human3.6M benchmark. Our technical insight is that, by jointly harnessing the epipolar geometry and human skeleton priors, 3-D joint estimation can boil down to an optimization problem over two sets of 2-D estimations. To our best knowledge, this represents the first work that collects high-quality 3-D human data via catadioptric systems. We have conducted comprehensive experiments on cross-scenario pose estimation and visualization analysis. The results strongly demonstrate the usefulness of our proposed DBM human poses.
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Lagunas, M. A., and G. Vazquez. "Focusing wideband arrays from 2-D spectral estimates." In Fifth ASSP Workshop on Spectrum Estimation and Modeling. IEEE, 1990. http://dx.doi.org/10.1109/spect.1990.205551.

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Choi, Sungyun, Beungjin Kim, George J. Cokkinides, and A. P. Sakis Meliopoulos. "Autonomous state estimation for the smart grid - laboratory implementation." In IEEE PES T&D 2010. IEEE, 2010. http://dx.doi.org/10.1109/tdc.2010.5484289.

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Ma, Jian, Yousu Chen, Zhenyu Huang, and Pak Chung Wong. "Using state estimation residuals to detect abnormal SCADA data." In IEEE PES T&D 2010. IEEE, 2010. http://dx.doi.org/10.1109/tdc.2010.5484686.

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Gandelli, A. "Spectrum estimation techniques to study quantization in A&D conversion systems." In Fifth ASSP Workshop on Spectrum Estimation and Modeling. IEEE, 1990. http://dx.doi.org/10.1109/spect.1990.205573.

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Negaharipour, S. "On 3-D motion estimation from 2-D sonar image flow." In OCEANS 2012. IEEE, 2012. http://dx.doi.org/10.1109/oceans.2012.6404919.

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Lv, Jianxun, Mahmoud A. Mohamed, Haiwen Yuan, and Bärbel Mertsching. "Dense Optical Flow Estimation from RGB-D." In 2018 Eighth International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC). IEEE, 2018. http://dx.doi.org/10.1109/imccc.2018.00076.

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Liu, Yongzhi, and Zhiping Lin. "2-D DOA estimation with virtual sensors." In 2015 IEEE International Conference on Digital Signal Processing (DSP). IEEE, 2015. http://dx.doi.org/10.1109/icdsp.2015.7252018.

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Yuen, P., N. Khalili, and F. Mokhtarian. "Curvature Estimation on Smoothed 3-D Meshes." In British Machine Vision Conference 1999. British Machine Vision Association, 1999. http://dx.doi.org/10.5244/c.13.14.

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Radhakrishnan, Chandrasekar, V. Chandrasekar, Wesley Berg, and Steven C. Reising. "Rainfall Estimation from Tempest-D Cubesat Observations." In IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021. http://dx.doi.org/10.1109/igarss47720.2021.9554052.

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Reports on the topic "D Estimation"

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Baker, Zachary Kent. Constrained Shortest Path Estimation on the D-Wave 2X: Accelerating Ionospheric Parameter Estimation Through Quantum Annealing. Office of Scientific and Technical Information (OSTI), November 2016. http://dx.doi.org/10.2172/1331299.

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Author, Not Given. R&D program benefits estimation: DOE Office of Electricity Delivery and Energy Reliability. Office of Scientific and Technical Information (OSTI), December 2006. http://dx.doi.org/10.2172/1216653.

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Nadiri, M. Ishaq, and Ingmar Prucha. Estimation of the Depreciation Rate of Physical and R&D Capital in the U.S. Total Manufacturing Sector. Cambridge, MA: National Bureau of Economic Research, December 1993. http://dx.doi.org/10.3386/w4591.

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Irwin, Douglas, and Peter Klenow. High Tech R&D Subsidies: Estimating the Effects of Sematech. Cambridge, MA: National Bureau of Economic Research, December 1994. http://dx.doi.org/10.3386/w4974.

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Lee, R. Estimating the Benefits of Government-Sponsored Energy R&D: Synthesis of Conference Discussions. Office of Scientific and Technical Information (OSTI), November 2003. http://dx.doi.org/10.2172/885698.

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Peters, Bettina, Mark Roberts, Van Anh Vuong, and Helmut Fryges. Estimating Dynamic R&D Demand: An Analysis of Costs and Long-Run Benefits. Cambridge, MA: National Bureau of Economic Research, August 2013. http://dx.doi.org/10.3386/w19374.

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Chensvert, Thomas L. NMR Reconstructive Elasticity Imaging of Breast: Surrogate Remote Palpation Using Quantitative 3-D Displacement and Strain Estimations. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada391282.

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Marshall, A. C. RSMASS-D models: An improved method for estimating reactor and shield mass for space reactor applications. Office of Scientific and Technical Information (OSTI), October 1997. http://dx.doi.org/10.2172/560867.

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Gordon, Roger, Mark Schankerman, and Richard Spady. Estimating the Effects of R&D on Bell System Productivity: A Model of Embodied Technical Change. Cambridge, MA: National Bureau of Economic Research, April 1985. http://dx.doi.org/10.3386/w1607.

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Functional and reserve capacities of an organism estimation among sprinters according to “D&K-TEST” indices and taking into account bioprofile. Ilsiyar Sh. Mutaeva , Chulpan A. Gizatullina , Aleksandra S. Seliverstova, September 2020. http://dx.doi.org/10.14526/2070-4798-2020-15-3-48-55.

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