Change Point Detection-Based Video Analysis

Surveillance cameras and sensors generate a large amount of data wherein there is scope for intelligent analysis of the video feed being received. The area is well researched but there are various challenges due to camera movement, jitter and noise. Change detection-based analysis of images is a fundamental step in the processing of the video feed, the challenge being determination of the exact point of change, enabling reduction in the time and effort in overall processing. It is a well-researched area; however, methodologies determining the exact point of change have not been explored fully. This area forms the focus of our current work. Most of the work till date in the area lies within the domain of applied methods to a pair or sequence of images. Our work focuses on application of change detection to a set of time-ordered images to identify the exact pair of bi-temporal images or video frames about the change point. We propose a metric to detect changes in time-ordered video frames in the form of rank-ordered threshold values using segmentation algorithms, subsequently determining the exact point of change. The results are applicable to general time-ordered set of images