抽象的な

DEVELOPMENT OF A HIGHLY EFFICIENT OBJECT TRACKING SYSTEM USING MODIFIED MEAN SHIFT TRACKING

Abhishek Kesharwani, Preeti Tuli

Object tracking is the process of locating a moving object (or multiple objects) over time using a camera. It has a variety of uses, some of which are: human-computer interaction, security and surveillance, video communication and compression, augmented reality, traffic control, medical imaging and video editing. Video tracking can be a time consuming process due to the amount of data that is contained in video. A lot of object tracking algorithms have been reported in literatures, but the area is still lacking with an efficient algorithm which can, not only track the objects but at the same time able to recognize the orientation and movement of object. In this paper an efficient object tracking system is proposed based on Modified mean shift tracking (MMST) algorithm. This 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 original mean shift tracking algorithm, the position of the target can be well estimated, while the scale and orientation changes cannot be adaptively estimated. This paper presents an efficient modification on available mean shift tracking technique, that the weight image derived from the target model and the candidate model can represent the possibility that a pixel belongs to the target, in this work it will be shown that the original mean shift tracking algorithm can be derived using the zeroth and the first order moments of the weight image.