Translator Disclaimer
Paper
3 March 2008 An algorithm for motion and change detection in image sequences based on chaos and information theory
Author Affiliations +
Proceedings Volume 6812, Image Processing: Algorithms and Systems VI; 68120K (2008) https://doi.org/10.1117/12.766934
Event: Electronic Imaging, 2008, San Jose, California, United States
Abstract
Accurate and robust image change detection and motion segmentation has been of substantial interest in the image processing and computer vision communities. To date no single motion detection algorithm has been universally superior while biological vision systems are so adept at it. In this paper, we analyze image sequences using phase plots generated from sequential image frames and demonstrate that the changes in pixel amplitudes due to the motion of objects in an image sequence result in phase space behaviour resembling a chaotic signal. Recent research in neural signals have shown biological neural systems are highly responsive to chaos-like signals resulting from aperiodic forcing functions caused by external stimuli. We then hypothesize an alternative physics-based motion algorithm from the traditional optical flow algorithm. Rather than modeling the motion of objects in an image as a flow of grayscale values as in optical flow, we propose to model moving objects in an image scene as aperiodic forcing functions, impacting the imaging sensor, be it biological or silicon-based. We explore the applicability of some popular measures for detecting chaotic phenomena in the frame-wise phase plots generated from sequential image pairs and demonstrate their effectiveness on detecting motion while robustly ignoring illumination change.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Farmer and C. Yuan "An algorithm for motion and change detection in image sequences based on chaos and information theory", Proc. SPIE 6812, Image Processing: Algorithms and Systems VI, 68120K (3 March 2008); https://doi.org/10.1117/12.766934
PROCEEDINGS
12 PAGES


SHARE
Advertisement
Advertisement
RELATED CONTENT

Multiscale self-similarity features of terrain surface
Proceedings of SPIE (May 12 2006)
Robust Estimation of Image Flow
Proceedings of SPIE (March 01 1990)
General motion estimation and segmentation
Proceedings of SPIE (September 01 1990)
New method for segmentation and motion field estimation
Proceedings of SPIE (August 26 1996)
Motion field computation with a continuation algorithm
Proceedings of SPIE (August 19 1997)

Back to Top