Video as input: spiral search with the sparse angular sampling

Authors:
Tatiana V. Evreinova;Grigori Evreinov;Roope Raisamo
Affiliations:
TAUCHI Computer-Human Interaction Unit, Department of Computer Sciences, University of Tampere, Finland;TAUCHI Computer-Human Interaction Unit, Department of Computer Sciences, University of Tampere, Finland;TAUCHI Computer-Human Interaction Unit, Department of Computer Sciences, University of Tampere, Finland
Venue:
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Year:
2006

Citing 2
Cited 0

Face Recognition: Features Versus Templates

IEEE Transactions on Pattern Analysis and Machine Intelligence
Face as Mouse Through Visual Face Tracking

CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents an improved cross-correlation algorithm for template-based object tracking: the reduced spiral search with a sparse angular sampling. The basic parameters of the algorithm for the real-time face tracking were evaluated regarding their impact on the algorithm performance. They are the minimum number of pixels and the size of the template, the correlation threshold and drifting, and the parameters of the search – radius, shift, direction, and rotation of the template. We demonstrated that the information provided by the grid-like template might be reduced to 16 pixels with a grid step of 15 pixels. A spiral search in 8 directions with a minimum shift of 1 pixel decreases the number of computations by 20 times. Being activated sequentially the template rotation does not increase the performance, but doing the tracking adaptive and robust.