Paper
17 January 2005 Instantaneous reliability assessment of motion features in surveillance videos
Author Affiliations +
Abstract
Although a tremendous effort has been made to perform a reliable analysis of images and videos in the past fifty years, the reality is that one cannot rely 100% on the analysis results. The only exception is applications in controlled environments as dealt in machine vision, where closed world assumptions apply. However, in general, one has to deal with an open world, which means that content of images may significantly change, and it seems impossible to predict all possible changes. For example, in the context of surveillance videos, the light conditions may suddenly fluctuate in parts of images only, video compression or transmission artifacts may occur, a wind may cause a stationary camera to tremble, and so on. The problem is that video analysis has to be performed in order to detect content changes, but such analysis may be unreliable due to the changes, and thus fail to detect the changes and lead to "vicious cycle". The solution pursuit in this paper is to monitor the reliability of the computed features by analyzing their general properties. We consider statistical properties of feature value distributions as well as temporal properties. Our main strategy is to estimate the feature properties when the features are reliable computed, so that any set of features that does not have these properties is detected as being unreliable. This way we do not perform any direct content analysis, but instead perform analysis of feature properties related to their reliability.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Longin Jan Latecki, Roland Miezianko, and Dragoljub Pokrajac "Instantaneous reliability assessment of motion features in surveillance videos", Proc. SPIE 5682, Storage and Retrieval Methods and Applications for Multimedia 2005, (17 January 2005); https://doi.org/10.1117/12.588003
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Video

Video surveillance

Motion measurement

Reliability

Motion detection

Principal component analysis

Video compression

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