An on-line visual human tracking algorithm using SURF-based dynamic object model

Author

Gupta, A. Meenakshi ; Garg, B. Sourav ; Kumar, C. Senthil ; Behera, D. Laxmidhar

Author_Institution

B.-C. Innovation Lab., A.-D. Indian Inst. of Technol. Kanpur (IITK), Kanpur, India

fYear

2013

fDate

15-18 Sept. 2013

Firstpage

3875

Lastpage

3879

Abstract

The interest point based tracking methods suffer from the limitation of unavailability of sufficient number of matching key points for the target in all frames of a running video. In this paper, a dynamic model is proposed for describing the object model which is used for tracking a human in a non-stationary video. This dynamic model takes into account the change in the pose as well as the motion of the human. A simple autoregression based predictor is used for dealing with the case of full occlusion. Simulation results are provided to show the efficacy of the algorithm.

Keywords

autoregressive processes; feature extraction; image matching; image motion analysis; image sequences; object tracking; pose estimation; video signal processing; SURF-based dynamic object model; full occlusion; human motion; human pose; interest point based tracking methods; key points matching; nonstationary video; online visual human tracking algorithm; running video; simple autoregression based predictor; speeded-up robust features; Auto-regression prediction; Human Tracking; SURF;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2013 20th IEEE International Conference on

Conference_Location

Melbourne, VIC

Type

conf

DOI

10.1109/ICIP.2013.6738798

Filename

6738798