Feature Fusion in Part-Based Object Detection

Abstract

In this study, classification of complex objects in images as a whole is compared with classification of its distinctive components using different features. In addition, the impact of feature fusion in part-based object detection is investigated. Applied method, implemented system, conducted tests and their results are presented in this paper. Test results show that, even in the case of a good segmentation, object components are classified more successfully compared to whole object and feature fusion method improves the obtained results to a certain degree.