Consumer Depth Cameras for Computer Vision
暂无分享,去创建一个
Andrea Fossati | Kurt Konolige | Helmut Grabner | Juergen Gall | Xiaofeng Ren | Juergen Gall | Xiaofeng Ren | K. Konolige | H. Grabner | A. Fossati
[1] Azriel Rosenfeld,et al. Computer Vision , 1988, Adv. Comput..
[2] Paul J. Besl,et al. A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..
[3] Richard M. Murray,et al. A Mathematical Introduction to Robotic Manipulation , 1994 .
[4] R. K. Shyamasundar,et al. Introduction to algorithms , 1996 .
[5] Janne Heikkilä,et al. A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[6] Rómer Rosales,et al. Inferring body pose without tracking body parts , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[7] John P. Lewis,et al. Pose Space Deformation: A Unified Approach to Shape Interpolation and Skeleton-Driven Deformation , 2000, SIGGRAPH.
[8] Trevor Darrell,et al. Fast pose estimation with parameter-sensitive hashing , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[9] Ian D. Reid,et al. Articulated Body Motion Capture by Stochastic Search , 2005, International Journal of Computer Vision.
[10] Jitendra Malik,et al. Twist Based Acquisition and Tracking of Animal and Human Kinematics , 2004, International Journal of Computer Vision.
[11] Trevor Darrell,et al. Avoiding the "streetlight effect": tracking by exploring likelihood modes , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[12] Adrian Hilton,et al. A survey of advances in vision-based human motion capture and analysis , 2006, Comput. Vis. Image Underst..
[13] Rómer Rosales,et al. Combining Generative and Discriminative Models in a Framework for Articulated Pose Estimation , 2006, International Journal of Computer Vision.
[14] Michael J. Black,et al. Combined discriminative and generative articulated pose and non-rigid shape estimation , 2007, NIPS.
[15] Richard Szeliski,et al. Modeling the World from Internet Photo Collections , 2008, International Journal of Computer Vision.
[16] Michael J. Black,et al. Detailed Human Shape and Pose from Images , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[17] Reinhard Koch,et al. Single View Motion Tracking by Depth and Silhouette Information , 2007, SCIA.
[18] Tamim Asfour,et al. Robust real-time stereo-based markerless human motion capture , 2008, Humanoids 2008 - 8th IEEE-RAS International Conference on Humanoid Robots.
[19] Behzad Dariush,et al. Controlled human pose estimation from depth image streams , 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.
[20] Cristian Sminchisescu,et al. Twin Gaussian Processes for Structured Prediction , 2010, International Journal of Computer Vision.
[21] Craig Gotsman,et al. Articulated Object Reconstruction and Markerless Motion Capture from Depth Video , 2008, Comput. Graph. Forum.
[22] Stefano Soatto,et al. Relevant Feature Selection for Human Pose Estimation and Localization in Cluttered Images , 2008, ECCV.
[23] Hans-Peter Seidel,et al. Markerless motion capture of man-machine interaction , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[24] Björn Stenger,et al. A Single Camera Motion Capture System for Human-Computer Interaction , 2008, IEICE Trans. Inf. Syst..
[25] Hans-Peter Seidel,et al. Stabilizing motion tracking using retrieved motion priors , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[26] Rüdiger Dillmann,et al. Fusion of 2d and 3d sensor data for articulated body tracking , 2009, Robotics Auton. Syst..
[27] Jovan Popović,et al. Real-time hand-tracking with a color glove , 2009, SIGGRAPH 2009.
[28] Michael J. Black,et al. Estimating human shape and pose from a single image , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[29] Amit Bleiweiss,et al. Markerless motion capture using a single depth sensor , 2009, SIGGRAPH ASIA '09.
[30] Hans-Peter Seidel,et al. Motion capture using joint skeleton tracking and surface estimation , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[31] Reinhard Koch,et al. Time-of-Flight Sensors in Computer Graphics , 2009, Eurographics.
[32] David J. Fleet,et al. Physics-Based Person Tracking Using the Anthropomorphic Walker , 2010, International Journal of Computer Vision.
[33] Hans-Peter Seidel,et al. Multilinear pose and body shape estimation of dressed subjects from image sets , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[34] Danica Kragic,et al. Hands in action: real-time 3D reconstruction of hands in interaction with objects , 2010, 2010 IEEE International Conference on Robotics and Automation.
[35] Kenny Erleben,et al. GPU Accelerated Likelihoods for Stereo-Based Articulated Tracking , 2010, ECCV Workshops.
[36] Sebastian Thrun,et al. Real-time identification and localization of body parts from depth images , 2010, 2010 IEEE International Conference on Robotics and Automation.
[37] Nassir Navab,et al. Manifold Learning for ToF-based Human Body Tracking and Activity Recognition , 2010, BMVC.
[38] Reinhard Koch,et al. Time-of-Flight sensor calibration for accurate range sensing , 2010, Comput. Vis. Image Underst..
[39] Vincent Lepetit,et al. From Canonical Poses to 3D Motion Capture Using a Single Camera , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[40] Raquel Urtasun,et al. Combining discriminative and generative methods for 3D deformable surface and articulated pose reconstruction , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[41] Sebastian Thrun,et al. Real time motion capture using a single time-of-flight camera , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[42] Gérard G. Medioni,et al. Human pose estimation from a single view point, real-time range sensor , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops.
[43] Ronald Poppe,et al. A survey on vision-based human action recognition , 2010, Image Vis. Comput..
[44] Jinxiang Chai,et al. VideoMocap: modeling physically realistic human motion from monocular video sequences , 2010, ACM Trans. Graph..
[45] Dieter Fox,et al. Sparse distance learning for object recognition combining RGB and depth information , 2011, 2011 IEEE International Conference on Robotics and Automation.
[46] Ruigang Yang,et al. Accurate 3D pose estimation from a single depth image , 2011, 2011 International Conference on Computer Vision.
[47] Andrew W. Fitzgibbon,et al. Efficient regression of general-activity human poses from depth images , 2011, 2011 International Conference on Computer Vision.
[48] Tomás Pajdla,et al. Multi-view reconstruction preserving weakly-supported surfaces , 2011, CVPR 2011.
[49] Luc Van Gool,et al. Functional categorization of objects using real-time markerless motion capture , 2011, CVPR 2011.
[50] Hans-Peter Seidel,et al. Fast articulated motion tracking using a sums of Gaussians body model , 2011, 2011 International Conference on Computer Vision.
[51] Adolfo López,et al. Real-time upper body tracking with online initialization using a range sensor , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).
[52] Toby Sharp,et al. Real-time human pose recognition in parts from single depth images , 2011, CVPR.
[53] Nassir Navab,et al. Estimating human 3D pose from Time-of-Flight images based on geodesic distances and optical flow , 2011, Face and Gesture 2011.
[54] Michael J. Black,et al. Home 3D body scans from noisy image and range data , 2011, 2011 International Conference on Computer Vision.
[55] Kourosh Khoshelham,et al. Accuracy analysis of kinect depth data , 2012 .
[56] Hans-Peter Seidel,et al. A data-driven approach for real-time full body pose reconstruction from a depth camera , 2011, 2011 International Conference on Computer Vision.
[57] Dieter Fox,et al. RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments , 2012, Int. J. Robotics Res..