Object tracking using background subtraction and motion estimation in MPEG videos

Authors:
Ashwani Aggarwal;Susmit Biswas;Sandeep Singh;Shamik Sural;A. K. Majumdar
Affiliations:
Indian Institute of Technology, Kharagpur, West Bengal, India;Indian Institute of Technology, Kharagpur, West Bengal, India;Indian Institute of Technology, Kharagpur, West Bengal, India;Indian Institute of Technology, Kharagpur, West Bengal, India;Indian Institute of Technology, Kharagpur, West Bengal, India
Venue:
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Year:
2006

Citing 4
Cited 3

Detecting Salient Motion by Accumulating Directionally-Consistent Flow

IEEE Transactions on Pattern Analysis and Machine Intelligence
Analysis of Camera Operations in MPEG Compressed Domain Based on Generalized Hough Transform

PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Video shot analysis using efficient multiple object tracking

ICMCS '97 Proceedings of the 1997 International Conference on Multimedia Computing and Systems
Real-time compressed-domain spatiotemporal segmentation and ontologies for video indexing and retrieval

IEEE Transactions on Circuits and Systems for Video Technology

An Approach to Trajectory Estimation of Moving Objects in the H.264 Compressed Domain

PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Compressed domain indexing of scalable H.264/SVC streams

Image Communication
Moving object tracking in H.264/AVC bitstream

MCAM'07 Proceedings of the 2007 international conference on Multimedia content analysis and mining

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a fast and robust method for moving object tracking directly in the compressed domain using features available in MPEG videos. DCT domain background subtraction in Y plane is used to locate candidate objects in subsequent I-frames after a user has marked an object of interest in the given frame. DCT domain histogram matching using Cb and Cr planes and motion vectors are used to select the target object from the set of candidate objects. The target object position is finally interpolated in the predicted frames to obtain a smooth tracking across GOPs.