Investigating 3D model and part information for improving content-based and attribute-based object retrieval
Yen-Liang Lin · 2012
Content-based and attribute-based image/object retrieval are the key techniques for managing and analyzing the exponentially growing media collections. However, due to large variations in viewing angle/position, illumination, occlusion, and background, traditional object retrieval is extremely challenging. This article discusses an ongoing research in investigating the value of 3D models and informative parts for the object retrieval system. To show the feasibility of the proposed method, we apply it to the problem of multi-view vehicle retrieval. Preliminary results on vehicle retrieval demonstrate that our approach significantly outperforms the prior content-based image retrieval (CBIR) methods. Motivated by the proposed method, we are now extending the framework to attribute-based retrieval system over other domains (e.g., people) with 3D information augmented by Kinect devices.