Generic Object Detection Based on Boosting Embedded with Bag-of-Words
Xue Na Qiu, Shi Rong Liu, Jia Tao Song · Applied Mechanics and Materials · 2011
This paper studies generic object detection. In the view of complexity and diversity of generic object, it proposes Boosting generic object detection method with bag-of-words. Boosting method has good detection efficiency, but it has some fault detections due to the diversity and complexity of the object. While Bag-of-words method has some advantages, such as local patch features, simplicity and robustness, and it has good classification performance of complex object. The proposed method applies Bag-of-words to remove the fault detection and to improve the tracking results of Boosting, and thus it achieves high generic object detection accuracy.