Abstract
This paper describes a method for video retrieval system based on local invariant region descriptors. A novel framework is proposed for combined video segmentation, content extraction and retrieval. A similarity measure, previously proposed by the authors based on local region features, is used for video segmentation. The local regions are tracked throughout a shot and stable features are extracted. The conventional key frame method is replaced with these stable local features to characterise different shots. A grouping technique is introduced to combine these stable tracks into meaningful object clusters. The above method can handle the different scales of object appearance in videos. Compared to previous video retrieval approaches, the proposed method is highly robust to camera and object motions and can withstand severe illumination changes. The proposed framework is applied to scene and object retrieval experiments and significant improvement in performance is demonstrated.
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