Conference Proceeding

Window-Matching Techniques with Kalman Filtering for an Improved Object Visual Tracking

Brasilia Univ., Brasilia
10/2007; DOI:10.1109/COASE.2007.4341822 pp.829 - 834 In proceeding of: Automation Science and Engineering, 2007. CASE 2007. IEEE International Conference on
Source: IEEE Xplore

ABSTRACT This paper describes the development and application of an algorithm for object visual tracking from a sequence of images. The algorithm is based on window-matching techniques using the sum of squared differences (SSD) as a distance-similarity measure, but adding stochastic filtering. The algorithm is then applied for tracking: a vehicle on an urban environment; two people meeting and walking together; a ball on a ping-pong game. It is concluded that incorporating the Kalman filtering greatly improves the tracking performance.

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Keywords

people meeting
 
ping-pong game
 
squared differences
 
SSD
 
tracking performance
 
urban environment
 
window-matching techniques