Unidimensional Multiscale Local Features for Object Detection Under Rotation and Mild Occlusions

Authors:
Michael Villamizar;Alberto Sanfeliu;Juan Andrade Cetto
Affiliations:
Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Llorens Artigas 4-6, 08028 Barcelona, Spain;Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Llorens Artigas 4-6, 08028 Barcelona, Spain;Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Llorens Artigas 4-6, 08028 Barcelona, Spain
Venue:
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Year:
2007

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Abstract

In this article, scale and orientation invariant object detection is performed by matching intensity level histograms. Unlike other global measurement methods, the present one uses a local feature description that allows small changes in the histogram signature, giving robustness to partial occlusions. Local features over the object histogram are extracted during a Boostinglearning phase, selecting the most discriminant features within a training histogram image set. The Integral Histogramhas been used to compute local histograms in constant time.