Designing and Implementation of an Efficient Object Tracking System Using Modified Mean Shift Tracking

Abstract: Because of image-databases and “live” video information is growing more and more widespread, their intelligent or automatic examining is becoming exceptionally important. Object tracking, in general, is a challenging problem. In this project work an efficient object tracking system is presented based on Modified mean shift tracking (MMST) algorithm. This project work basically deals with how to address the problem to estimate the scale and orientation changes of the target under the mean shift tracking framework. In the mean shift tracking algorithm, the location of the target can be sound estimated, though the scale and orientation changes cannot be adaptively estimated. Taking into consideration that the weight image derived from the target model and the candidate model can represent the possibility that a pixel belongs to the target. The proposed method adaptively estimates the height, width, and orientation changes of the target. Experiments are performed to testify the proposed method and validate its robustness to the scale and orientation changes of the target.

Keywords: Object Tracking, Modified mean shift tracking (MMST) algorithm, scale and orientation changes, Mean shift tracking framework, target model, candidate model.