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Real-time human pose recognition in parts from single depth images

by Jamie Shotton, Andrew Fitzgibbon, Mat Cook, Toby Sharp, Mark Finocchio, Richard Moore, Alex Kipman, Andrew Blake - IN CVPR , 2011
"... We propose a new method to quickly and accurately predict 3D positions of body joints from a single depth image, using no temporal information. We take an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler p ..."
Abstract - Cited by 568 (17 self) - Add to MetaCart
We propose a new method to quickly and accurately predict 3D positions of body joints from a single depth image, using no temporal information. We take an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler

From Few to many: Illumination cone models for face recognition under variable lighting and pose

by Athinodoros S. Georghiades, Peter N. Belhumeur, David J. Kriegman - IEEE Transactions on Pattern Analysis and Machine Intelligence , 2001
"... We present a generative appearance-based method for recognizing human faces under variation in lighting and viewpoint. Our method exploits the fact that the set of images of an object in fixed pose, but under all possible illumination conditions, is a convex cone in the space of images. Using a smal ..."
Abstract - Cited by 754 (12 self) - Add to MetaCart
We present a generative appearance-based method for recognizing human faces under variation in lighting and viewpoint. Our method exploits the fact that the set of images of an object in fixed pose, but under all possible illumination conditions, is a convex cone in the space of images. Using a

Histograms of Oriented Gradients for Human Detection

by Navneet Dalal, Bill Triggs - In CVPR , 2005
"... We study the question of feature sets for robust visual object recognition, adopting linear SVM based human detection as a test case. After reviewing existing edge and gradient based descriptors, we show experimentally that grids of Histograms of Oriented Gradient (HOG) descriptors significantly out ..."
Abstract - Cited by 3735 (9 self) - Add to MetaCart
are all important for good results. The new approach gives near-perfect separation on the original MIT pedestrian database, so we introduce a more challenging dataset containing over 1800 annotated human images with a large range of pose variations and backgrounds. 1

A Survey of Computer Vision-Based Human Motion Capture

by Thomas B. Moeslund, Erik Granum - Computer Vision and Image Understanding , 2001
"... A comprehensive survey of computer vision-based human motion capture literature from the past two decades is presented. The focus is on a general overview based on a taxonomy of system functionalities, broken down into four processes: initialization, tracking, pose estimation, and recognition. Each ..."
Abstract - Cited by 515 (14 self) - Add to MetaCart
A comprehensive survey of computer vision-based human motion capture literature from the past two decades is presented. The focus is on a general overview based on a taxonomy of system functionalities, broken down into four processes: initialization, tracking, pose estimation, and recognition. Each

Behavior recognition via sparse spatio-temporal features

by Piotr Dollár, Vincent Rabaud, Garrison Cottrell, Serge Belongie - In VS-PETS , 2005
"... A common trend in object recognition is to detect and leverage the use of sparse, informative feature points. The use of such features makes the problem more manageable while providing increased robustness to noise and pose variation. In this work we develop an extension of these ideas to the spatio ..."
Abstract - Cited by 717 (4 self) - Add to MetaCart
A common trend in object recognition is to detect and leverage the use of sparse, informative feature points. The use of such features makes the problem more manageable while providing increased robustness to noise and pose variation. In this work we develop an extension of these ideas

Detecting faces in images: A survey

by Ming-hsuan Yang, David J. Kriegman, Narendra Ahuja - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2002
"... Images containing faces are essential to intelligent vision-based human computer interaction, and research efforts in face processing include face recognition, face tracking, pose estimation, and expression recognition. However, many reported methods assume that the faces in an image or an image se ..."
Abstract - Cited by 839 (4 self) - Add to MetaCart
Images containing faces are essential to intelligent vision-based human computer interaction, and research efforts in face processing include face recognition, face tracking, pose estimation, and expression recognition. However, many reported methods assume that the faces in an image or an image

Towards Unified Human Parsing and Pose Estimation

by Jian Dong, Qiang Chen, Xiaohui Shen, Jianchao Yang, Shuicheng Yan
"... We study the problem of human body configuration anal-ysis, more specifically, human parsing and human pose es-timation. These two tasks, i.e. identifying the semantic re-gions and body joints respectively over the human body image, are intrinsically highly correlated. However, pre-vious works gener ..."
Abstract - Cited by 4 (3 self) - Add to MetaCart
We study the problem of human body configuration anal-ysis, more specifically, human parsing and human pose es-timation. These two tasks, i.e. identifying the semantic re-gions and body joints respectively over the human body image, are intrinsically highly correlated. However, pre-vious works

Pose Machines: Articulated Pose Estimation via Inference Machines

by Varun Ramakrishna, Daniel Munoz, Martial Hebert, J. Andrew Bagnell, Yaser Sheikh
"... Abstract. State-of-the-art approaches for articulated human pose es-timation are rooted in parts-based graphical models. These models are often restricted to tree-structured representations and simple parametric potentials in order to enable tractable inference. However, these simple dependencies fa ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Abstract. State-of-the-art approaches for articulated human pose es-timation are rooted in parts-based graphical models. These models are often restricted to tree-structured representations and simple parametric potentials in order to enable tractable inference. However, these simple dependencies

Stochastic Tracking of 3D Human Figures Using 2D Image Motion

by Hedvig Sidenbladh, Michael J. Black, D. J. Fleet - In European Conference on Computer Vision , 2000
"... . A probabilistic method for tracking 3D articulated human gures in monocular image sequences is presented. Within a Bayesian framework, we de ne a generative model of image appearance, a robust likelihood function based on image graylevel dierences, and a prior probability distribution over pose an ..."
Abstract - Cited by 383 (33 self) - Add to MetaCart
. A probabilistic method for tracking 3D articulated human gures in monocular image sequences is presented. Within a Bayesian framework, we de ne a generative model of image appearance, a robust likelihood function based on image graylevel dierences, and a prior probability distribution over pose

3-D model-based tracking of humans in action: a multi-view approach

by D. M. Gavrila, L. S. Davis , 1996
"... We present a vision system for the 3-D model-based tracking of unconstrained human movement. Using image sequences acquired simultaneously from multiple views, we recover the 3-D body pose at each time instant without the use of markers. The pose recovery problem is formulated as a search problem ..."
Abstract - Cited by 355 (9 self) - Add to MetaCart
We present a vision system for the 3-D model-based tracking of unconstrained human movement. Using image sequences acquired simultaneously from multiple views, we recover the 3-D body pose at each time instant without the use of markers. The pose recovery problem is formulated as a search problem
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