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IBPRIA
2007
Springer

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

9 years 4 months ago
Unidimensional Multiscale Local Features for Object Detection Under Rotation and Mild Occlusions
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 Boosting learning phase, selecting the most discriminant features within a training histogram image set. The Integral Histogram has been used to compute local histograms in constant time.
Michael Villamizar, Alberto Sanfeliu, Juan Andrade
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where IBPRIA
Authors Michael Villamizar, Alberto Sanfeliu, Juan Andrade-Cetto
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