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Bosov, A. A., V. M. Ilman, and N. V. Khalipova. "MULTIPLE OBJECTS." Science and Transport Progress. Bulletin of Dnipropetrovsk National University of Railway Transport, no. 3(57) (July 2, 2015): 145–61. http://dx.doi.org/10.15802/stp2015/46075.
Morgan, Jane L., and Antje S. Meyer. "Processing of Extrafoveal Objects During Multiple-Object Naming." Journal of Experimental Psychology: Learning, Memory, and Cognition 31, no. 3 (2005): 428–42. http://dx.doi.org/10.1037/0278-7393.31.3.428.
In psychology and neuroscience, multiple object tracking (MOT) refers to the ability of humans and other animals to simultaneously monitor multiple objects as they move. It is also the term for a laboratory technique used to study this ability. In an MOT study, a number of identical moving objects are presented on a display. Some of the objects are designated as targets while the rest serve as distractors. Study participants try to monitor the changing positions of the targets as they and the distractors move about. At the end of the trial, participants typically are asked to indicate the final positions of the targets. The results of MOT experiments have revealed dramatic limitations on humans' ability to simultaneously monitor multiple moving objects. For example, awareness of features such as color and shape is disrupted by the objects' movement.
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Hirano, Masahiro, Keigo Iwakuma, and Yuji Yamakawa. "Multiple High-Speed Vision for Identical Objects Tracking." Journal of Robotics and Mechatronics 34, no. 5 (October 20, 2022): 1073–84. http://dx.doi.org/10.20965/jrm.2022.p1073.
In multi-object tracking of identical objects, it is difficult to return to tracking after occlusions occur due to three-dimensional intersections between objects because the objects cannot be distinguished by their appearances. In this paper, we propose a method for multi-object tracking of identical objects using multiple high-speed vision systems. By using high-speed vision, we take advantage of the fact that tracking information, such as the position of each object in each camera and the presence or absence of occlusion, can be obtained with high time density. Furthermore, we perform multi-object tracking of identical objects by efficiently performing occlusion handling using geometric constraints satisfied by multiple high-speed vision systems; these can be used by appropriately positioning them with respect to the moving region of the object. Through experiments using table-tennis balls as identical objects, this study shows that stable multi-object tracking can be performed in real time, even when frequent occlusions occur.
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Ayare, Shubhamkar, and Nisheeth Srivastava. "Multiple Object Tracking Without Pre-attentive Indexing." Open Mind 8 (2024): 278–308. http://dx.doi.org/10.1162/opmi_a_00128.
Abstract Multiple object tracking (MOT) involves simultaneous tracking of a certain number of target objects amongst a larger set of objects as they all move unpredictably over time. The prevalent explanation for successful target tracking by humans in MOT involving visually identical objects is based on the Visual Indexing Theory. This assumes that each target is indexed by a pointer using a non-conceptual mechanism to maintain an object’s identity even as its properties change over time. Thus, successful tracking requires successful indexing and the absence of identification errors. Identity maintenance and successful tracking are measured in terms of identification (ID) and tracking accuracy respectively, with higher accuracy indicating better identity maintenance or better tracking. Existing evidence suggests that humans have high tracking accuracy despite poor identification accuracy, suggesting that it might be possible to perform MOT without indexing. Our work adds to existing evidence for this position through two experiments, and presents a computational model of multiple object tracking that does not require indexes. Our empirical results show that identification accuracy is aligned with tracking accuracy in humans for tracking up to three, but is lower when tracking more objects. Our computational model of MOT without indexing accounts for several empirical tracking accuracy patterns shown in earlier studies, reproduces the dissociation between tracking and identification accuracy produced earlier in the literature as well as in our experiments, and makes several novel predictions.
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Franconeri, S. L., J. Halberda, L. Feigenson, and G. A. Alvarez. "Common fate can define objects in multiple object tracking." Journal of Vision 4, no. 8 (August 1, 2004): 365. http://dx.doi.org/10.1167/4.8.365.
Ogawa, H., and A. Yagi. "The processing of untracked objects during multiple object tracking." Journal of Vision 2, no. 7 (March 15, 2010): 242. http://dx.doi.org/10.1167/2.7.242.
Category-level object recognition is a fundamental capability for the potential use of robots in the assistance of humans in useful tasks. There have been numerous vision-based object recognition systems yielding fast and accurate results in constrained environments. However, by depending on visual cues, these techniques are susceptible to object variations in size, lighting, rotation, and pose, all of which cannot be avoided in real video data. Thus, the task of object recognition still remains very challenging.
My thesis work builds upon the fact that robots can observe humans interacting with the objects in their environment. We refer to the set of objects, which can be involved in the interaction as `interactionable' objects. The interaction of humans with the `interactionable' objects provides numerous nonvisual cues to the identity of objects.
In this thesis, I will introduce a flexible object recognition approach called Multiple-Cue Object Recognition (MCOR) that can use multiple cues of any predefined type, whether they are cues intrinsic to the object or provided by observation of a human. In pursuit of this goal, the thesis will provide several contributions: A representation for the multiple cues including an object definition that allows for the flexible addition of these cues; Weights that reflect the various strength of association between a particular cue and a particular object using a probabilistic relational model, as well as object displacement values for localizing the information in an image; Tools for defining visual features, segmentation, tracking, and the values for the non-visual cues; Lastly, an object recognition algorithm for the incremental discrimination of potential object categories.
We evaluate these contributions through a number of methods including simulation to demonstrate the learning of weights and recognition based on an analytical model, an analytical model that demonstrates the robustness of the MCOR framework, and recognition results on real video data using a number of datasets including video taken from a humanoid robot (Sony QRIO), video captured from a meeting setting, scripted scenarios from outside universities, and unscripted TV cooking data.
Using the datasets, we demonstrate the basic features of the MCOR algorithm including its ability to use multiple cues of different types. We demonstrate the applicability of MCOR to an outside dataset. We show that MCOR has better recognition results over vision-only recognition systems, and show that performance only improves with the addition of more cue types.
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Ramalingam, Chitra. "Modeling Multiple Granularities of Spatial Objects." Fogler Library, University of Maine, 2002. http://www.library.umaine.edu/theses/pdf/RamalingamC2002.pdf.
De, Vaal Jan Hendrik. "Metric reconstruction of multiple rigid objects." Thesis, Stellenbosch : University of Stellenbosch, 2009. http://hdl.handle.net/10019.1/2892.
Thesis (MScEng (Mathematical Sciences. Applied Mathematics))--University of Stellenbosch, 2009. Engineers struggle to replicate the capabilities of the sophisticated human visual
system. This thesis sets out to recover motion and 3D structure of multiple rigid
objects up to a similarity. The motion of these objects are either recorded in a
single video sequence, or images of the objects are recorded on multiple, di erent
cameras. We assume a perspective camera model with optional provision for
calibration information. The Structure from Motion (SfM) problem is addressed
from a matrix factorization point of view. This leads to a reconstruction correct
up to a projectivity of little use in itself. Using techniques from camera autocalibration
the projectivity is upgraded to a similarity. This reconstruction
is also applied to multiple objects through motion segmentation. The SfM
system developed in this thesis is a batch-processing algorithm, requiring few
frames for a solution and readily accepts images from very di erent viewpoints.
Since a solution can be obtained with just a few frames, it can be used to
initialize sequential methods with slower convergence rates, such as the Kalman
lter. The SfM system is critically evaluated against an extensive set of motion
sequences.
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Thórhallsson, Torfi. "Symmetric objects in multiple affine views." Thesis, University of Oxford, 2000. http://ora.ox.ac.uk/objects/uuid:49ec4596-7086-4645-81f8-8dacf48b694a.
This thesis is concerned with the utilization of object symmety as a cue for segmentation and object recognition. In particular it investigates the problem of detecting 3D bilaterally symmetric objects from affine views. The first part of the thesis investigates the problem of detecting 3D bilateral symmetry within a scene from known point correspondences across two or more affine views. We begin by extending the notion of skewed symmetry to three dimensions, and give a definition in terms of degenerate structure that applies equally to an affine 3D structure or to point correspondences across two or more affine views. We then consider the effects of measurement errors on symmetry detection, and derive an optimal statistical test of degenerate structure, and thereby of 3D-skewed symmetry. We then move on to the problem of searching for 3D skewed symmetric sets within a larger scene. We discuss two approaches to the problem, both of which we have implemented, and we demonstrate fully automatic detection of 3D skewed symmetry on images of uncluttered scenes. We conclude the first part by investing means of verifying the presence of bilateral rather than skewed symmetry in the Euclidean space, by enforcing mutual consistency between multiple skewed symmetric sets, and by drawing on partial knowledge about the camera calibration. The second part of the thesis is concerned with the problem of obtaining feature correspondences across multiple affine views, as required for the detection of symmetry. In particular we investigate the geometric matching constraints that exist between affine views. We start by specilizing the four projective multifocal tensors to the affine case, and use these to carry the bulk of all known projective multi-view matching relations to affine views, unearthing some new relations in the process. Having done that, we address the problem of estimating the affine tensors. We provide a minimal set of constraints on the affine trifocal tensor, and search for ways of estimating the affine tensors from point and line correspondences.
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Titsias, Michalis. "Unsupervised learning of multiple objects in images." Thesis, University of Edinburgh, 2005. http://hdl.handle.net/1842/776.
Developing computer vision algorithms able to learn from unsegmented images containing multiple objects is important since this is how humans constantly learn from visual experiences. In this thesis we consider images containing views of multiple objects and our task is to learn about each of the objects present in the images. This task can be approached as a factorial learning problem, where each image is explained by instantiating a model for each of the objects present with the correct instantiation parameters. A major problem with learning a factorial model is that as the number of objects increases, there is a combinatorial explosion of the number of configurations that need to be considered. We develop a greedy algorithm to extract object models sequentially from the data by making use of a robust statistical method, thus avoiding the combinatorial explosion. When we have video data, we greatly speed up the greedy algorithm by carrying out approximate tracking of the multiple objects in the scene. This method is applied to raw image sequence data and extracts the objects one at a time. First, the (possibly moving) background is learned, and moving objects are found at later stages. The algorithm recursively updates an appearance model so that occlusion is taken into account, and matches this model to the frames through the sequence. We apply this method to learn multiple objects in image sequences as well as articulated parts of the human body. Additionally, we learn a distribution over parts undergoing full affine transformations that expresses the relative movements of the parts. The idea of fitting a model to data sequentially using robust statistics is quite general and it can be applied to other models. We describe a method for training mixture models by learning one component at a time and thus building the mixture model in a sequential manner. We do this by incorporating an outlier component into the mixture model which allows us to fit just one data cluster by "ignoring" the rest of the clusters. Once a model is fitted we remove from consideration all the data explained by this model and then repeat the operation. This algorithm can be used to provide a sensible initialization of the mixture components when we train a mixture model.
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Ye, Lin. "The Perception of Objects with Multiple Affordances." Miami University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=miami1165554317.
Denna avhandling har skrivits i sammarbete med en Stockholmsbaserat konst- och designstudio vid namn ''Humans since 1982'' som bygger och säljer modern högteknologisk konst till marknader världen över. Studion ville utföra forskning kring att utveckla och implementera ett system som detekterade och beräknade positionen av två roterande oberoende objekt monterade på två stegmotorer via en växellåda. Produkten där lösningen skulle implementeras ställde olika tekniska och designmässiga krav på implementationen. De viktigaste kraven var att lösningen skulle klara en noggrannhet på ±1° med en precision på 99.95 %. Hastigheten för objekten som detekterades var minst 50 [steg/sekund] och distansen mellan objekten och detektionsutrustning var minst 20 [mm]. En barriär av ett ometalliskt material skiljde objekten och motorerna samt den drivande elektroniken åt, vilket i kombination med en komplicerad växellåda förhindrade användandet av IR baserade lösningar, rotationsenkoders eller mekaniska kalibreringsmetoder. Olika möjliga tekniska lösningar i form av kapasitans- induktions- och radiobaserade detektionsmetoder undersöktes. En lösning baserat på Hall-element och permanenta Neodymium magneter föreslogs, designades, implementerades och testades. Två olika algoritmer för automatisk detektion och kalibrering föreslogs och testades. Den första algoritmen var baserad på att röra båda objekten samtidigt och den andra var baserad på att röra ett objekt i taget. Den andra algoritmen visades vara mest optimal med avseende på tid, robusthet och noggrannhet och efter implementation på hårdvaruplatformen (som bestod av en 32-bit ARM Cortex mikro kontroller) åstadkom den en noggrannhet på ± 0.8° med en precision på 99.97 %. Självkalibreringen tog 92.6 [s] och konsumerade i genomsnitt 34.56 % av processor cyklerna. Applikationen tog då upp 85.93 % av RAM-minnet och 13.74 % av flash minnet inkluderat ett realtidsoperativsystem samt bibliotek för att extrahera testdatan. This thesis project has been developed in conjunction with a Stockholm based art studio called ''Humans since 1982''. The studio builds and sells contemporary and highly technological luxury art pieces all over the world. The company wanted to perform research towards developing and implementing a solution that detected and determined the position of two independent objects being rotated by two stepper motors and a gearbox. This thesis investigates possible proximity sensor solutions and their applicability and accuracy for this application. The requirements of the solution are to perform detection of two rotating loads driven by stepper motors at about 50 [steps/second] at a distance of 20 [mm] from any sensing electronics within the accuracy of ±1° with a precision of 99.95 %. The loads were mounted in such a way that they were not in line of sight from the driving motor or electronics and a complex unmodifiable gearbox prevented simple solutions such as IR-based sensors, rotary encoders and mechanical stoppers to be used. Multiple detection options such as capacitive-, inductive-, and radio based methods were investigated. A technical solution based on Hall elements and permanent Neodymium magnets was proposed, designed, implemented and tested. Two algorithms for automatic load detection and calibration were proposed and tested. The first algorithm detected the loads while both were moving simultaneously and the second detected one load at a time. The second algorithm proved to be the best solution with respect to time, robustness and accuracy and it was able to achieve an accuracy of 0.8° at a precision of 99.97 % and it was implemented on the target embedded system. The self-calibration took 92.6 [s] with an average CPU utilization of 34.56 %, consumed 85.93 % of the MCU RAM and 13.74 % of the Flash memory including a real-time operating system and drivers for extraction of test data on a 32-bit ARM Cortex micro controller.
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Muschter, Evelyn. "Constructing multiple objects across space and time." Doctoral thesis, Università degli studi di Trento, 2018. https://hdl.handle.net/11572/368612.
For us to interact with our environment we must have an understanding of the location and properties of the objects within it over time. Incoming stimuli from different sensory modalities continuously provide information. In order to create a coherent percept, it is necessary to combine these sensory signals in the brain into a single representation of an object or event. Temporal integration, the process of combining information over time is one important prerequisite for it. Likewise, multisensory integration, the process of combining information from different sensory modalities to generate a coherent percept is of great importance. Furthermore, as our environment is not static but dynamic it is necessary to combine sensory information over time and space. Despite, the ever-increasing neuroscientific results, much about the underlying brain mechanisms remains unknown. This thesis describes an effort of understanding how sensory information are integrated in the brain and what effects attention has on how we integrate multiple objects in space and time.
Chapter 1 introduces the reader to the existing literature on neural oscillations, specifically alpha band frequency, which is hypothesized to play a critical role in temporal processing and attention. This is followed by a review of the literature on temporal integration and the theoretical background of multisensory integration. The following chapters will report the three studies conducted: Chapter 2 describes the first study, a MEG study that investigates the role of alpha oscillations in temporal integration. Chapter 3 reports the second MEG study, which focuses the role of attention to modality in multisensory integration. Chapter 4 presents the third study, a behavioral oscillations study, which focuses on the role of neural oscillations in selective attention in a dynamic scene. Finally, Chapter 5 summarizes all the findings from this research.
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Muschter, Evelyn. "Constructing multiple objects across space and time." Doctoral thesis, University of Trento, 2018. http://eprints-phd.biblio.unitn.it/2984/1/thesis_Evelyn_Muschter_final.pdf.
For us to interact with our environment we must have an understanding of the location and properties of the objects within it over time. Incoming stimuli from different sensory modalities continuously provide information. In order to create a coherent percept, it is necessary to combine these sensory signals in the brain into a single representation of an object or event. Temporal integration, the process of combining information over time is one important prerequisite for it. Likewise, multisensory integration, the process of combining information from different sensory modalities to generate a coherent percept is of great importance. Furthermore, as our environment is not static but dynamic it is necessary to combine sensory information over time and space. Despite, the ever-increasing neuroscientific results, much about the underlying brain mechanisms remains unknown. This thesis describes an effort of understanding how sensory information are integrated in the brain and what effects attention has on how we integrate multiple objects in space and time.
Chapter 1 introduces the reader to the existing literature on neural oscillations, specifically alpha band frequency, which is hypothesized to play a critical role in temporal processing and attention. This is followed by a review of the literature on temporal integration and the theoretical background of multisensory integration. The following chapters will report the three studies conducted: Chapter 2 describes the first study, a MEG study that investigates the role of alpha oscillations in temporal integration. Chapter 3 reports the second MEG study, which focuses the role of attention to modality in multisensory integration. Chapter 4 presents the third study, a behavioral oscillations study, which focuses on the role of neural oscillations in selective attention in a dynamic scene. Finally, Chapter 5 summarizes all the findings from this research.
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Cichocki, Radoslaw. "Classification of objects in images based on various object representations." Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5774.
Object recognition is a hugely researched domain that employs methods derived from mathematics, physics and biology. This thesis combines the approaches for object classification that base on two features – color and shape. Color is represented by color histograms and shape by skeletal graphs. Four hybrids are proposed which combine those approaches in different manners and the hybrids are then tested to find out which of them gives best results. Mail the author at radoslaw.cichocki(at)gmail.com
Grimson, William Eric Leifur. Sensing strategies for disambiguating among multiple objects in known poses. Cambridge, Mass: Massachusetts Institute of Technology.Artificial Intelligence Laboratory, 1985.
Lexier, Micah. I'm thinking of a number: Selected invitations, books, catalogues, packaged prints, objects in multiple, t-shirts, projects in and for publications, coins, and other printed matter, 1980-2010. Halifax, N.S: Press of the Nova Scotia College of Art and Design, 2010.
United States. Bureau of Land Management. Medford District. Cascade-Siskiyou National Monument: A plan for studying the impacts of livestock grazing on the objects of biological interest. Medford, Or: The Office, 2005.
Streit, Roy, Robert Blair Angle, and Murat Efe. Analytic Combinatorics for Multiple Object Tracking. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-61191-0.
Zhou, Linfei, Wei Ye, Zhen Wang, Claudia Plant, and Christian Böhm. "Indexing Multiple-Instance Objects." In Lecture Notes in Computer Science, 143–57. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64471-4_13.
Hollink, Vera, Maarten van Someren, and Viktor de Boer. "Clustering Objects from Multiple Collections." In KI 2009: Advances in Artificial Intelligence, 136–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04617-9_18.
Rühl, Tim, and Henri E. Bal. "Synchronizing operations on multiple objects." In Lecture Notes in Computer Science, 135–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-64359-1_684.
Mackellar, Bonnie K., and Joan Peckham. "Multiple Perspectives of Design Objects." In Artificial Intelligence in Design ’98, 87–106. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5121-4_5.
Hruŝka, Tomáŝ, and Petr Kolenĉík. "Extending an object-oriented model: Multiple class objects." In Conceptual Modeling — ER '97, 229–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63699-4_19.
Chen, Ke-Yin, Chung-Lin Huang, Shih-Chung Hsu, and I.-Cheng Chang. "Multiple Objects Tracking across Multiple Non-Overlapped Views." In Advances in Image and Video Technology, 128–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25346-1_12.
Nishino, Ko, and Katsushi Ikeuchi. "Robust Simultaneous Registration of Multiple Range Images." In Digitally Archiving Cultural Objects, 71–88. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-75807_5.
Oishi, Takeshi, Atsushi Nakazawa, Ryo Kurazume, and Katsushi Ikeuchi. "A Fast Simultaneous Alignment of Multiple Range Images." In Digitally Archiving Cultural Objects, 89–107. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-75807_6.
Тези доповідей конференцій з теми "Multiple objects":
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Guler, Sadiye, Jason A. Silverstein, and Ian H. Pushee. "Stationary objects in multiple object tracking." In 2007 IEEE Conference on Advanced Video and Signal Based Surveillance. IEEE, 2007. http://dx.doi.org/10.1109/avss.2007.4425318.
Beigzadeh, Borhan, Ali Meghdari, and Yasan Beigzadeh. "Dynamic Manipulation of Objects Using Multiple Manipulators." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-41481.
In this study, we explore the possibility of dynamic object manipulation of objects using a series of manipulators. Here, two three-active-link manipulators have been considered and the generality of the idea to a series of manipulator is developed easily. So without any gripper, and in an unstable grasp manner, we try to throw an object by a manipulator and catch it with another. Also we can consider the impacts generated in the moment of throwing and catching objects, as some disturbance and therefore we damp it. Finally we deal with the whole manipulation process as a system with some noise and disturbance and try to demonstrate its stability. All results have been validated with the aid of simulations.
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Matos, Hamilton, Pollyana Mustaro, and Ismar Silveira. "MILO - A Proposal of Multiple Intelligences Learning Objects." In InSITE 2007: Informing Science + IT Education Conference. Informing Science Institute, 2007. http://dx.doi.org/10.28945/3137.
Learning objects-driven approaches for the development of instructional content have been widely used to structure entire courses and repositories for distinct learning contexts. Nonetheless, their use is still done in a static, non-adaptive manner, since students are presented to prebuilt compilations of learning object having few or none relationship with its learning current conditions, history or personal learning style, which together compose the student momentum. This work presents an analysis of current instructional design and multiple intelligences theories in order to create learning objects that provide adaptive learning methods according to different students’ characteristics. Using technologies that allow such dynamic approaches, it was created -as a proof of concept - a learning object about the Pythagorean Theorem.
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Sang Chia, Alex Yong, and Weimin Huang. "Multiple Objects Trackingwith Multiple Hypotheses Dynamic Updating." In 2006 International Conference on Image Processing. IEEE, 2006. http://dx.doi.org/10.1109/icip.2006.312399.
Bergey, Dana J., James P. Mills, and Steven K. Rogers. "Multiple aperture optical imaging." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1986. http://dx.doi.org/10.1364/oam.1986.ma6.
The effect of multiple aperture systems on coherent and incoherent optical imaging was analyzed. Most of the effort was concentrated on the coherent imaging case. A computer program was developed that predicted the images of several simple objects as viewed through various types of multiple aperture. Objects such as edges, bars, and circles were chosen since more complicated objects can be thought of as a collection of these simple objects. These multiaperture images were produced and photographed in the laboratory. The photographs and the computer-generated plots are then analyzed to determine how the spacing, size, and number of subapertures affect the image. These images are compared and contrasted to determine what information can be obtained from them. Essential information, such as shape, orientation, position, and dimensions of the object, was looked for. Finally, the effects of the same multiple apertures on incoherent imaging are studied, and the results are compared with those of the coherent case.
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Ji, L., N. Schulz, M. Nowak, H. Marshall, Ye-Fei Yuan, Xiang-Dong Li, and Dong Lai. "Multiple High-resolution Chandra Grating Observations of Her X-1." In ASTROPHYSICS OF COMPACT OBJECTS: International Conference on Astrophysics of Compact Objects. AIP, 2008. http://dx.doi.org/10.1063/1.2840405.
Lee, Chun-Tse, Cheng-Han Tsai, and Jen-Yuan (James) Chang. "A CAD-Free Random Bin Picking System for Fast Changeover on Multiple Objects." In ASME 2020 29th Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/isps2020-1911.
Abstract Random bin picking (RBP) has been a popular research topic due to the demand of industry 4.0, techniques like object detection, picking strategies and robot motion planning are more and more important. Much of the existing research uses the CAD model of the workpiece as the database. However, building CAD models is time-consuming and not all objects have CAD models. In this paper, a CAD-free random bin picking system is proposed to pick miscellaneous objects. By using Mask-RCNN instance segmentation, the object’s category and pickable area can be determined within a 2D image captured from RGB-D camera. Then, the pixels of pickable area can be converted into point clouds for picking tasks with the depth data of RGB-D camera. Compared with traditional RBP systems, a system with the Mask-RCNN doesn’t need to create CAD models, and it only requires fewer images of stacked objects (less than 50) and heuristic picking points labelling as the training data. Thus, the RBP systems which proposed in this paper can lowers the barriers to introduce the random bin picking system into factories. Through this scheme, a fast changeover for different objects could be made within 10 hours. The experiment results show that this system could pick two different objects with high success rate and acceptable cycle time. This system provides a useful and efficient solution for the industrial automation implementations that require bin picking.
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Pu, Kejia, Zhichao Lian, and Zhongeng Liu. "Multiple objects tracking based on multiple information integration." In 2017 International Conference on Progress in Informatics and Computing (PIC). IEEE, 2017. http://dx.doi.org/10.1109/pic.2017.8359543.
Alex Yong Sang Chia, Weimin Huang, and Liyuan Li. "Multiple Objects Tracking with Multiple Hypotheses Graph Representation." In 18th International Conference on Pattern Recognition (ICPR'06). IEEE, 2006. http://dx.doi.org/10.1109/icpr.2006.843.
Bernat, Andrew, and Stephen Riter. "Automatic Tracking Of Multiple Objects." In SPIE 1989 Technical Symposium on Aerospace Sensing, edited by Mohan M. Trivedi. SPIE, 1989. http://dx.doi.org/10.1117/12.969263.
Erdmann, Michael, and Thomas Lozano-Perez. On Multiple Moving Objects. Fort Belvoir, VA: Defense Technical Information Center, May 1986. http://dx.doi.org/10.21236/ada196213.
Jaspan, Ciera, and Jonathan Aldrich. Checking Temporal Relations between Multiple Objects. Fort Belvoir, VA: Defense Technical Information Center, June 2008. http://dx.doi.org/10.21236/ada485514.
Edelman, Shimon, and Daphna Weinshall. A Self-Organizing Multiple-View Representation of Three-Dimensional Objects. Fort Belvoir, VA: Defense Technical Information Center, August 1989. http://dx.doi.org/10.21236/ada216711.
Moelich, M. Autonomous Motion Segmentation of Multiple Objects in Low Resolution Video Using Variational Level Sets. Office of Scientific and Technical Information (OSTI), November 2003. http://dx.doi.org/10.2172/15013642.
Sivers, E. A. Use of multiple CT scans to accommodate large objects and stretch dynamic range of detectability. Office of Scientific and Technical Information (OSTI), September 1994. http://dx.doi.org/10.2172/34396.
A novel algorithmic framework for the robust detection and classification of machinery threats and other potentially harmful objects intruding onto a pipeline right-of-way (ROW) is designed from three perspectives: visibility improvement, context-based segmentation, and object recognition/classification. In the first part of the framework, an adaptive image enhancement algorithm is utilized to improve the visibility of aerial imagery to aid in threat detection. In this technique, a nonlinear transfer function is developed to enhance the processing of aerial imagery with extremely non-uniform lighting conditions. In the second part of the framework, the context-based segmentation is developed to eliminate regions from imagery that are not considered to be a threat to the pipeline. Context based segmentation makes use of a cascade of pre-trained classifiers to search for regions that are not threats. The context based segmentation algorithm accelerates threat identification and improves object detection rates. The last phase of the framework is an efficient object detection model. Efficient object detection �follows a three-stage approach which includes extraction of the local phase in the image and the use of local phase characteristics to locate machinery threats. The local phase is an image feature extraction technique which partially removes the lighting variance and preserves the edge information of the object. Multiple orientations of the same object are matched and the correct orientation is selected using feature matching by histogram of local phase in a multi-scale framework. The classifier outputs locations of threats to pipeline.�The advanced automatic image analysis system is intended to be capable of detecting construction equipment along the ROW of pipelines with a very high degree of accuracy in comparison with manual threat identification by a human analyst. �
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Krainyk, Yaroslav M., Anzhela P. Boiko, Dmytro A. Poltavskyi, and Vladimir I. Zaselskiy. Augmented Reality-based historical guide for classes and tourists. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3747.
In this paper, development of historical guide based on Augmented Reality (AR) technology is considered. The developed guide application it targeted to be used in different scenarios, in particular, during history learning classes, for guidance of the tourists to exhibits both indoor and outdoor. Common features of all these scenarios are generalized and according to them main information and objects model for forming scene are identified. This part is followed by detailed description of objects and scene representation, markers usage, employment of additional services, etc. Finally, the developed historical guide application has been introduced. It harnesses A-Frame library for processing of models and their representation. The application is able to work with different markers so that it can be extended easily. In addition, one of the main benefits of the developed application is support of multiple platforms because it works from web-browser and does not require installation of additional software. The developed application can be effectively used for all provided scenarios and has potential for further extension.
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Badia, R., J. Ejarque, S. Böhm, C. Soriano, and R. Rossi. D4.4 API and runtime (complete with documentation and basic unit testing) for IO employing fast local storage. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.9.001.
This deliverable presents the activities performed on the ExaQUte project task 4.5 Development of interface to fast local storage. The activities have been focused in two aspects: reduction of the storage space used by applications and design and implementation of an interface that optimizes the use of fast local storage by MPI simulations involved in the project applications. In the rst case, for one of the environments involved in the project (PyCOMPSs) the default behavior is to keep all intermediate les until the end of the execution, in case these les are reused later by any additional task. In the case of the other environment (HyperLoom), all les are deleted by default. To unify these two behaviours, the calls \delete object" and \detele le"have been added to the API and a ag \keep" that can be set to true to keep the les and objects that maybe needed later on. We are reporting results on the optimization of the storage needed by a small case of the project application that reduces the storage needed from 25GB to 350MB. The second focus has been on the de nition of an interface that enables the optimization of the use of local storage disk. This optimization focuses on MPI simulations that may be executed across multiple nodes. The added annotation enables to de ne access patters of the processes in the MPI simulations, with the objective of giving hints to the runtime of where to allocate the di erent MPI processes and reduce the data transfers, as well as the storage usage.
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Lecumberry, Federico, Alvaro Pardo, and Guillermo Sapiro. Simultaneous Object Classification and Segmentation with High-Order Multiple Shape Models. Fort Belvoir, VA: Defense Technical Information Center, May 2009. http://dx.doi.org/10.21236/ada513239.
Dodge, M., and B. Ray. Definitions of Managed Object Extensions for Very High Speed Digital Subscriber Lines (VDSL) Using Multiple Carrier Modulation (MCM) Line Coding. RFC Editor, May 2005. http://dx.doi.org/10.17487/rfc4070.
