Literatura académica sobre el tema "Landmark Estimation"
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Artículos de revistas sobre el tema "Landmark Estimation"
Sakai, Atsushi, Teppei Saitoh y Yoji Kuroda. "Robust Landmark Estimation and Unscented Particle Sampling for SLAM in Dynamic Outdoor Environment". Journal of Robotics and Mechatronics 22, n.º 2 (20 de abril de 2010): 140–49. http://dx.doi.org/10.20965/jrm.2010.p0140.
Texto completoLiu, Shengli, Xiaowen Zhu, Zewei Cao y Gang Wang. "Deep 1D Landmark Representation Learning for Space Target Pose Estimation". Remote Sensing 14, n.º 16 (18 de agosto de 2022): 4035. http://dx.doi.org/10.3390/rs14164035.
Texto completoFujii, Hajime, Yoshinobu Ando, Takashi Yoshimi y Makoto Mizukawa. "Shape Recognition of Metallic Landmark and its Application to Self-Position Estimation for Mobile Robot". Journal of Robotics and Mechatronics 22, n.º 6 (20 de diciembre de 2010): 718–25. http://dx.doi.org/10.20965/jrm.2010.p0718.
Texto completoFloreskul, Volodymyr, Konstantin Tretyakov y Marlon Dumas. "Memory-Efficient Fast Shortest Path Estimation in Large Social Networks". Proceedings of the International AAAI Conference on Web and Social Media 8, n.º 1 (16 de mayo de 2014): 91–100. http://dx.doi.org/10.1609/icwsm.v8i1.14532.
Texto completoFong, Li Wei, Pi Ching Lou y Ke Jia Tang. "Vehicle Kinematic State Estimation Using Passive Sensor Fusion Approach". Applied Mechanics and Materials 271-272 (diciembre de 2012): 1709–12. http://dx.doi.org/10.4028/www.scientific.net/amm.271-272.1709.
Texto completoMohd Shah, Hairol Nizam, Zalina Kamis, Azhar Ahmad, Mohd Rizuan Baharon, Muhd Akmal Noor Rajikon y Kang Hui Hwa. "Vision Based Position Control for Vertical Take-off and Landing (VTOL) Using One Singular Landmark". Modern Applied Science 13, n.º 9 (22 de agosto de 2019): 33. http://dx.doi.org/10.5539/mas.v13n9p33.
Texto completoChen, Yao Chang, Ta Ming Shih y Chung Ho Wang. "Stereo Vision Specific Observation Model for EKF-Based SLAM". Applied Mechanics and Materials 373-375 (agosto de 2013): 238–41. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.238.
Texto completoHsu, Chen-Chien, Cheng-Kai Yang, Yi-Hsing Chien, Yin-Tien Wang, Wei-Yen Wang y Chiang-Heng Chien. "Computationally efficient algorithm for vision-based simultaneous localization and mapping of mobile robots". Engineering Computations 34, n.º 4 (12 de junio de 2017): 1217–39. http://dx.doi.org/10.1108/ec-05-2015-0123.
Texto completoD’Amelio, Richard y Thomas J. Dunn. "Revisiting the Santa Barbara sense of direction scale, mental rotations, and gender differences in spatial orientation". PsyPag Quarterly 1, n.º 115 (junio de 2020): 7–10. http://dx.doi.org/10.53841/bpspag.2020.1.115.7.
Texto completoChen, Haiwen, Jin Chen, Zhuohuai Guan, Yaoming Li, Kai Cheng y Zhihong Cui. "Stereovision-Based Ego-Motion Estimation for Combine Harvesters". Sensors 22, n.º 17 (25 de agosto de 2022): 6394. http://dx.doi.org/10.3390/s22176394.
Texto completoTesis sobre el tema "Landmark Estimation"
Soh, Ling Min. "Recognition using tagged objects". Thesis, University of Surrey, 2000. http://epubs.surrey.ac.uk/844110/.
Texto completoLuo, Chong. "Driver's Gaze Zone Estimation in Realistic Driving Environment by Kinect". Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38076.
Texto completoZhao, Sanqiang. "On Sparse Point Representation for Face Localisation and Recognition". Thesis, Griffith University, 2009. http://hdl.handle.net/10072/366629.
Texto completoThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Griffith School of Engineering
Science, Environment, Engineering and Technology
Full Text
Alqahtani, Faleh Mohammed A. "Three-dimensional facial tracker using a stereo vision system". Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/131825/1/Faleh%20Mohammed%20A_Alqahtani_Thesis.pdf.
Texto completoLandmann, Tobias [Verfasser]. "A case study for Skukuza: Estimating biophysical properties of fires using EOS-MODIS satellite data : A field and remote sensing study to quantify burnt area and fire effects in South African semi-arid savannas / Tobias Landmann". Aachen : Shaker, 2004. http://d-nb.info/1172610657/34.
Texto completoZemánek, Ondřej. "Počítání vozidel v statickém obraze". Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-417211.
Texto completoCruz, Daniel Filipe Gonçalves. "Automatic anatomical landmark location estimation in orthopedics". Master's thesis, 2021. http://hdl.handle.net/10316/98097.
Texto completoA Artroplastia total do joelho (ATJ) é um procedimento cirúrgico que consiste na substituição da região articular do joelho por uma prótese do joelho. Foram investigados e desenvolvidos sistemas de navegação baseados em computadores para melhorar o resultados destes procedimento cirúrgicos. Estes sistemas ajudam o cirurgião em planear a posição mais adequada para as próteses e auxiliam-no durante o procedimento cirúrgico a seguir da forma mais eficiente o plano cirúrgico definido.Esta tese é desenvolvida na recente introdução de sistemas de navegação por vídeo para ATJ e é focada em navegação image-free. Este tipo de navegação, requer a aquisição de determinadas pontos de referência anatómicas durante a cirurgia. No entanto, muitas vezes o processo de identificação destes pontos de referência é realizado manualmente, o que é demorado, tem falta de precisão e alta variabilidade, levando a erros significativos no posicionamento das próteses. Este trabalho apresenta uma pipeline para deteção e localização automática dos pontos de referência a partir de imagens RGB capturadas durante a cirurgia. O objetivo é guiar e assistir cirurgiões em localizar os pontos de referência fornecendo sugestões em tempo real sobre a localização dos mesmos. A solução proposta é baseada em algoritmos do estado da arte de deep learning, que combinamos com uma estratégia rápida e eficiente de gerar dados de treino que desenvolvemos especificamente para o nosso problema. Os resultados experimentais obtidos utilizando dados de cirurgias reais revelam um desempenho promissor, apresentando capacidade de generalização para diferentes dados intra-operatórios e estimações confiáveis que atendem aos requisitos clínicos e funciona em tempo real.
Total knee arthroplasty (TKA) is a surgical procedure that consists in replacing the entire knee joint by artificial knee implants. Computer-based navigation systems have been investigated and developed to improve the outcome of TKA procedures. These systems support the surgeon in planning the most adequate position for the implants, and assist during the procedure in effectively following the defined surgical plan. This thesis is built on the recent introduction of video-based navigation systems in the context of TKA and is focused on image-free navigation. This type of navigation requires the acquisition of particular anatomical landmarks intra-operatively. The accurate localization of these anatomical landmarks is essential for the success of the surgery. However, the landmark identification process is often conducted manually, which is time-consuming, lacks accuracy and has high variability, leading to significant errors in implant positioning. This work presents an end-to-end pipeline for automatic detection and localization of anatomical landmarks from RGB images acquired during the surgery. The aim is to guide and assist surgeons in locating the anatomical landmarks by providing real time suggestions about the landmark location. The proposed solution is based in state-of-the-art deep learning strategies, which we combine with a fast and effective labelling framework which we developed specifically to provide the required annotations. The experimental results using real surgery data show encouraging performance, presenting generelization capabilities for unseen data and reliable predictions that meet the clinical requirements, running in real-time.
Cheng, Yi-Tseng y 鄭亦曾. "Landmark Oriented Generalized Biologically Inspired Features for Age Estimation". Thesis, 2016. http://ndltd.ncl.edu.tw/handle/75001536503865780052.
Texto completo國立臺灣科技大學
機械工程系
104
We propose the Generalized Biologically Inspired Features (GBIFs) and a moving segmentation scheme followed by soft boundary regression for age estimation. The GBIF is more advantageous than the Bio-Inspired Feature (BIF) for capturing age-related facial traits. The moving segmentation is proposed to better determine the age groups, leading to an improvement on the age estimation accuracy. Different from most approaches that segment the age groups in an ad-hoc way, the moving segmentation allows one to define age groups using the local minima in the misclassification rate across ages. The extraction of the GBIF depends on the partition of component regions defined by facial landmarks. In addition to the partition of component regions, we also study the appropriate age grouping and hierarchical classification, and determine the best configuration for age estimation. The proposed approach with the most appropriate settings outperforms most of the state of the art on two benchmarks, FG-NET and MORPH.
Honari, Sina. "Feature extraction on faces : from landmark localization to depth estimation". Thèse, 2018. http://hdl.handle.net/1866/22658.
Texto completoKarmali, Tejan. "Landmark Estimation and Image Synthesis Guidance using Self-Supervised Networks". Thesis, 2022. https://etd.iisc.ac.in/handle/2005/5899.
Texto completoLibros sobre el tema "Landmark Estimation"
Ramsay, James. Curve registration. Editado por Frédéric Ferraty y Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.9.
Texto completoDesai, Anjali y Andrew S. Epstein. Doctors’ Prognostic Accuracy in Terminally Ill Patients (DRAFT). Editado por Nathan A. Gray y Thomas W. LeBlanc. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190658618.003.0031.
Texto completoCapítulos de libros sobre el tema "Landmark Estimation"
Lee, Donghoon, Junyoung Chung y Chang D. Yoo. "Joint Estimation of Pose and Face Landmark". En Computer Vision -- ACCV 2014, 305–19. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16817-3_20.
Texto completoLiu, Yin, Ying Cui y Zhong Jin. "Neighborhood-Preserving Estimation Algorithm for Facial Landmark Points". En Intelligent Science and Intelligent Data Engineering, 630–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36669-7_77.
Texto completoSommer, Stefan, Alexis Arnaudon, Line Kuhnel y Sarang Joshi. "Bridge Simulation and Metric Estimation on Landmark Manifolds". En Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics, 79–91. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67675-3_8.
Texto completoPayer, Christian, Martin Urschler, Horst Bischof y Darko Štern. "Uncertainty Estimation in Landmark Localization Based on Gaussian Heatmaps". En Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis, 42–51. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60365-6_5.
Texto completoGalindo, Ramiro, Wilbert G. Aguilar y Rolando P. Reyes Ch. "Landmark Based Eye Ratio Estimation for Driver Fatigue Detection". En Intelligent Robotics and Applications, 565–76. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27541-9_46.
Texto completoWu, Hongbo, Chris Bailey, Parham Rasoulinejad y Shuo Li. "Automatic Landmark Estimation for Adolescent Idiopathic Scoliosis Assessment Using BoostNet". En Medical Image Computing and Computer Assisted Intervention − MICCAI 2017, 127–35. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66182-7_15.
Texto completoAvisdris, Netanell, Leo Joskowicz, Brian Dromey, Anna L. David, Donald M. Peebles, Danail Stoyanov, Dafna Ben Bashat y Sophia Bano. "BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes". En Lecture Notes in Computer Science, 279–89. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-16440-8_27.
Texto completoYu, Yu, Gang Liu y Jean-Marc Odobez. "Deep Multitask Gaze Estimation with a Constrained Landmark-Gaze Model". En Lecture Notes in Computer Science, 456–74. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11012-3_35.
Texto completoSarkar, Rajib, Siddhartha Bhattacharyya, Debashis De y Asit K. Datta. "Landmark Identification from Low-Resolution Real-Time Image for Pose Estimation". En Lecture Notes in Electrical Engineering, 1–15. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8477-8_1.
Texto completoTrusheim, Felix, Alexandru Condurache y Alfred Mertins. "Visual Landmark Based 3D Road Course Estimation with Black Box Variational Inference". En Computer Analysis of Images and Patterns, 332–43. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64689-3_27.
Texto completoActas de conferencias sobre el tema "Landmark Estimation"
Suganya, S. y Narasimhan Ranga Raajan. "Augmented reality-landmark estimation". En 2011 International Conference on Recent Advancements in Electrical, Electronics and Control Engineering (ICONRAEeCE). IEEE, 2011. http://dx.doi.org/10.1109/iconraeece.2011.6129793.
Texto completoBurgos-Artizzu, Xavier P., Pietro Perona y Piotr Dollar. "Robust Face Landmark Estimation under Occlusion". En 2013 IEEE International Conference on Computer Vision (ICCV). IEEE, 2013. http://dx.doi.org/10.1109/iccv.2013.191.
Texto completoFarrokhsiar, Morteza y Homayoun Najjaran. "Rao-Blackwellized Particle Filter Approach to Monocular vSLAM With a Modified Initialization Scheme". En ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87610.
Texto completoLiu, Hong, Meijia Song, Wei Shi y Xia Li. "Position Constraint Loss For Fashion Landmark Estimation". En ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9054508.
Texto completoWen, Zhihua y Michael Rabinovich. "Network distance estimation with dynamic landmark triangles". En the 2008 ACM SIGMETRICS international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1375457.1375507.
Texto completoLim, Jihu, Dohun Kim, Sanghyun Park y Joonki Paik. "Face Landmark Estimation-based De-identification System". En 2022 International Conference on Electronics, Information, and Communication (ICEIC). IEEE, 2022. http://dx.doi.org/10.1109/iceic54506.2022.9748390.
Texto completoCivir, Cevdet y Cihan Topal. "Robust Landmark Selection for 3D Face Pose Estimation". En 2019 27th Signal Processing and Communications Applications Conference (SIU). IEEE, 2019. http://dx.doi.org/10.1109/siu.2019.8806384.
Texto completoLi, Ming, Zhonghua Liu, Jianan Huang y Kenji Imou. "Landmark direction angle estimation based on omnidirectional image". En 2010 International Conference on Information and Automation (ICIA). IEEE, 2010. http://dx.doi.org/10.1109/icinfa.2010.5512316.
Texto completoChin, Yi y Chun-Jen Tsai. "Bayesian dense motion field estimation with landmark constraint". En 2010 17th IEEE International Conference on Image Processing (ICIP 2010). IEEE, 2010. http://dx.doi.org/10.1109/icip.2010.5652489.
Texto completoWerner, Philipp, Frerk Saxen y Ayoub Al-Hamadi. "Landmark based head pose estimation benchmark and method". En 2017 IEEE International Conference on Image Processing (ICIP). IEEE, 2017. http://dx.doi.org/10.1109/icip.2017.8297015.
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