Universal Classifier: Adaptive Object Recognition for Multiple Domains

2015 Fiscal Year Final Research Report

• Project/Area Number: 25330215
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Perceptual information processing
• Research Institution: Kinki University
• Principal Investigator: HABE Hitoshi 近畿大学, 理工学部, 講師 (80346072)
• Project Period (FY): 2013-04-01 – 2016-03-31
• Keywords: 物体認識 / 性別推定 / Random Forests

Outline of Final Research Achievements

Image- and video-based object recognition usually requires a large amount of training data for sufficient performance. However, it is not always possible to obtain such a large dataset. Hence, we propose a method for extracting useful classifiers from a set of existing classifiers that is obtained by using training data of other scenes. Combining the extracted classifiers enables us to achieve better performance than solely using training data of a new scene. Experimental results show the effectiveness of the proposed method.

Free Research Field

コンピュータビジョン，物体認識