Detecting Salient Motion by Accumulating Directionally-Consistent Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Linear System Theory and Design
Linear System Theory and Design
Linear Systems
International Journal of Computer Vision
Non-parametric Model for Background Subtraction
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Segmenting Foreground Objects from a Dynamic Textured Background via a Robust Kalman Filter
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
Improved Adaptive Gaussian Mixture Model for Background Subtraction
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
A Principled Approach to Detecting Surprising Events in Video
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Probabilistic Kernels for the Classification of Auto-Regressive Visual Processes
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
ACM Computing Surveys (CSUR)
Improved seam carving for video retargeting
ACM SIGGRAPH 2008 papers
Detection and segmentation of moving objects in complex scenes
Computer Vision and Image Understanding
Spatiotemporal Saliency in Dynamic Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion-based background subtraction using adaptive kernel density estimation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Object Tracking in Structured Environments for Video Surveillance Applications
IEEE Transactions on Circuits and Systems for Video Technology
Video saliency detection with robust temporal alignment and local-global spatial contrast
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval
Temporal saliency for fast motion detection
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume Part I
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Detection of the motion of foreground objects on the backdrop of constantly changing and complex visuals has always been challenging. The motion of foreground objects, which is termed as salient motion, is marked by its predictability compared to the more complex unpredictable motion of the backgrounds like fluttering of leaves, ripples in water, smoke filled environments etc. We introduce a novel approach to detect this salient motion based on the control theory concept of 'observability' from the outputs, when the video sequence is represented as a linear dynamical system. The resulting algorithm is tested on a set of challenging sequences and compared to the state-of-the-art methods to showcase its superior performance on grounds of its computational efficiency and detection capability of the salient motion.