Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
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
Efficient Visual Event Detection Using Volumetric Features
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Individual Recognition Using Gait Energy Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Successive Convex Matching for Action Detection
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Behavior recognition via sparse spatio-temporal features
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
A new representation for human gait recognition: motion silhouettes image (MSI)
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Machine Recognition of Human Activities: A Survey
IEEE Transactions on Circuits and Systems for Video Technology
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Challenges of human behavior understanding
HBU'10 Proceedings of the First international conference on Human behavior understanding
Eigenspace-based fall detection and activity recognition from motion templates and machine learning
Expert Systems with Applications: An International Journal
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
Ongoing human action recognition with motion capture
Pattern Recognition
A real-time system for motion retrieval and interpretation
Pattern Recognition Letters
Matching mixtures of curves for human action recognition
Computer Vision and Image Understanding
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Recognizing human actions is an important topic in the computer vision community. One of the challenges of recognizing human actions is describing for the variability that arises when arbitrary view camera captures human performing actions. In this paper, we propose a spatio-temporal silhouette representation, called silhouette energy image (SEI), and multiple variability action models, to characterize motion and shape properties for automatic recognition of human actions in daily life. To address the variability in the recognition of human actions, several parameters, such as anthropometry of the person, speed of the action, phase (starting and ending state of an action), camera observations (distance from camera, slanting motion, and rotation of human body), and view variations are proposed. We construct the variability (or adaptable) models based on SEI and the proposed parameters. Global motion descriptors express the spatio-temporal properties of combined energy templates (SEI and variability action models). Our construction of the optimal model for each action and view is based on the support vectors of global motion descriptions of action models. We recognize different daily human actions of different styles successfully in the indoor and outdoor environment. Our experimental results show that the proposed method of human action recognition is robust, flexible and efficient.