Moving Object Detection and Tracking

Abstract

The detection of moving objects in videos is very important in many video processing applications and background modeling is often an indispensable process to achieve this goal.Most of the traditional background modeling methods utilize color or texture information.However, color information is sensitive to illumination variations and texture information cannot be utilized to separate smooth foreground from smooth background in most cases.A new integration framework of texture and color information for background modeling, in which the foreground decision equation includes three parts (one part for color information, one part for texture information and the left part for the integration of color and texture information).This framework is able to combine the advantages of texture and color features while inhibiting their disadvantages as well.A block based method to accelerate the background modeling.Specifically, in the texture information modeling process, a single histogram model is established for each block whose bins indicate the occurrence probabilities of different patterns, which is different from the traditional multi-histogram model for block-based background modeling, and then dominant background patterns are selected to calculate the background likelihood of new coming blocks.Dynamic background and multimodal problems can be handled through this technique.