The visual analysis of human movement: a survey
Computer Vision and Image Understanding
Human motion analysis: a review
Computer Vision and Image Understanding
The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Estimating the fundamental matrix by transforming image points in projective space
Computer Vision and Image Understanding
View-Invariant Representation and Recognition of Actions
International Journal of Computer Vision
Recognizing and Tracking Human Action
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Invariant features for 3-D gesture recognition
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Model-based tracking of self-occluding articulated objects
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Recognizing Action at a Distance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Silhouette Analysis-Based Gait Recognition for Human Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the use of Anthropometry in the Invariant Analysis of Human Actions
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Strike a Pose: Tracking People by Finding Stylized Poses
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Exploring the Space of a Human Action
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Periodic Motion Detection and Segmentation via Approximate Sequence Alignment
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Using Bilinear Models for View-invariant Action and Identity Recognition
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Tracking people and recognizing their activities
Tracking people and recognizing their activities
HMM-based Human Action Recognition Using Multiview Image Sequences
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Abnormal Walking Gait Analysis Using Silhouette-Masked Flow Histograms
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Matching actions in presence of camera motion
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Free viewpoint action recognition using motion history volumes
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Learning to Recognize Activities from the Wrong View Point
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Human Activity Recognition with Metric Learning
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
View-Independent Action Recognition from Temporal Self-Similarities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Making action recognition robust to occlusions and viewpoint changes
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Action recognition in broadcast tennis video using optical flow and support vector machine
ECCV'06 Proceedings of the 2006 international conference on Computer Vision in Human-Computer Interaction
Cross-view action recognition via view knowledge transfer
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Discriminative virtual views for cross-view action recognition
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Max-margin early event detectors
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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In this paper, we fully investigate the concept of fundamental ratios, demonstrate their application and significance in view-invariant action recognition, and explore the importance of different body parts in action recognition. A moving plane observed by a fixed camera induces a fundamental matrix F between two frames, where the ratios among the elements in the upper left 2x2 submatrix are herein referred to as the fundamental ratios. We show that fundamental ratios are invariant to camera internal parameters and orientation, and hence can be used to identify similar motions of line segments from varying viewpoints. By representing the human body as a set of points, we decompose a body posture into a set of line segments. The similarity between two actions is therefore measured by the motion of line segments and hence by their associated fundamental ratios. We further investigate to what extent a body part plays a role in recognition of different actions and propose a generic method of assigning weights to different body points. Experiments are performed on three categories of data: the controlled CMU MoCap dataset, the partially controlled IXMAS data, and the more challenging uncontrolled UCF-CIL dataset collected on the internet. Extensive experiments are reported on testing (i) view-invariance, (ii) robustness to noisy localization of body points, (iii) effect of assigning different weights to different body points, (iv) effect of partial occlusion on recognition accuracy, and (v) determining how soon our method recognizes an action correctly from the starting point of the query video.