Fast object detection using local feature-based SVMs

Viola-Jones approach to object detection is by far the most widely used object detection technique because of speed of detection in images with clutter. SVM-based object detection techniques have the disadvantage of slow detection speeds because of exhaustive window search. Appearance-based detection techniques do not generalize well in the presence of pose variations. In this paper, we propose a feature-based technique which classifies salient-points as belonging to object or background classes and performs object detection based on classified key points. Since keypoints are sparse, the technique is very fast. The use of SIFT descriptor provides invariance to scale and pose changes.