The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting Salient Motion by Accumulating Directionally-Consistent Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Signal Processing for Computer Vision
Signal Processing for Computer Vision
International Journal of Computer Vision
Motion detection with nonstationary background
Machine Vision and Applications
Statistical Background Subtraction for a Mobile Observer
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Background Modeling and Subtraction of Dynamic Scenes
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Robust Real-Time Face Detection
International Journal of Computer Vision
Bayesian Modeling of Dynamic Scenes for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spatiotemporal Saliency: Towards a Hierarchical Representation of Visual Saliency
Attention in Cognitive Systems
Spatiotemporal Saliency in Dynamic Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Spacetime Texture Representation and Recognition Based on a Spatiotemporal Orientation Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Action bank: A high-level representation of activity in video
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Action Spotting and Recognition Based on a Spatiotemporal Orientation Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Early delineation of the most salient portions of a temporal image stream (e.g., a video) could serve to guide subsequent processing to the most important portions of the data at hand. Toward such ends, the present paper documents an algorithm for spatiotemporal salience detection. The algorithm is based on a definition of salient regions as those that differ from their surrounding regions, with the individual regions characterized in terms of 3D, (x,y,t), measurements of visual spacetime orientation. The algorithm has been implemented in software and evaluated empirically on a publically available database for visual salience detection. The results show that the algorithm outperforms a variety of alternative algorithms and even approaches human performance.