Title :
Feature fusion in part-based object detection
Author :
Koyuncu, Murat ; Cetinkaya, Basar
Author_Institution :
Bilisim Sistemleri Muhendisligi Bolumu, Atilim Univ., Ankara, Turkey
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.
Keywords :
image classification; image fusion; image segmentation; object detection; complex objects; feature fusion method; part-based object detection; Computer vision; Feature extraction; Histograms; Object detection; Pattern recognition; Support vector machines; Transform coding; Component based object detection; SVM; feature vectors; fusion;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location :
Malatya
DOI :
10.1109/SIU.2015.7129887
