Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
A State-Based Approach to the Representation and Recognition of Gesture
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human motion analysis: a review
Computer Vision and Image Understanding
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Saliency, Scale and Image Description
International Journal of Computer Vision
Distortion Invariant Object Recognition in the Dynamic Link Architecture
IEEE Transactions on Computers
A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Recognizing Action at a Distance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Actions Sketch: A Novel Action Representation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Detecting Irregularities in Images and in Video
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Video Behaviour Profiling and Abnormality Detection without Manual Labelling
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Informative Shape Representations for Human Action Recognition
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Detecting unusual activity in video
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Gesture recognition using quadratic curves
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
A survey on visual surveillance of object motion and behaviors
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Image Processing
Event-based unobtrusive authentication using multi-view image sequences
Proceedings of the first ACM international workshop on Analysis and retrieval of tracked events and motion in imagery streams
Spatiotemporal analysis of human activities for biometric authentication
Computer Vision and Image Understanding
Exploratory search of long surveillance videos
Proceedings of the 20th ACM international conference on Multimedia
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In this paper, we propose a novel motion representation and apply it to abnormality detection and behavior recognition. At first, pointwise correspondences for the foreground in two consecutive video frames are established by performing a salient-region-based pointwise matching algorithm. Then, based on the established pointwise correspondences, a pointwise motion image (PMI) for each frame is built up to represent the motion status of the foreground. The PMI is more suitable for video analysis as it encapsulates a variety of motion information such as pointwise motion speed, pointwise motion orientation, pointwise motion duration, as well as the global shape of the foreground. In addition, it represents all of these pieces of information by a color image in the HSV space, by which many popular techniques in the image processing field can be straightforwardly adopted. By combining the PMI and AdaBoost, a method for abnormality detection and behavior recognition is proposed. The proposed method is shown to possess a high discriminative ability and is capable of dealing with local motion, global motion, and similar motions with different speeds. Experiments including a comparison with two existing methods demonstrate the effectiveness of the proposed representation in abnormality detection and behavior recognition.