A Survey on Moving Object Detection and Tracking

Select Volume / Issue:

• Volume 2,Issue 1, Jan. 2014

Year:

2014

Type of Publication:

Article

Keywords:

Object Detection, Background Subtraction, Temporal Frame Differencing, Object Tracking, Video Surveillance, Statistical Method

Authors:

Ashwani Kumar; Sudhanshu Kumar Mishra; Subhendu Kumar Behera; Jeevan Mishra

Journal:

IJISM

Volume:

2

Number:

1

Pages:

114-118

Month:

January

Abstract:

Object tracking in dynamic scenario is one of the most promising research areas in computer vision. It has a wide range of applications which include surveillance, performance analysis, video indexing, smart interfaces, teleconferencing etc. Robust and real time moving object tracking is a problematic issue in the area of computer vision. In object detection methodology, different methods have already been developed by researchers. But the object detection and tracking problem is still a sensitive issue in computer vision, and provide a lot of research opportunity in this area. This paper presents a survey of various techniques related to object detection and tracking. The main goal of this paper is to review the tracking methods, classify them into different categories, and to identify new trends. This paper is an attempt to accentuate on recent and robust methods for object detection and tracking.

Full text: IJISM_44_Final.pdf [Bibtex]