Title :
A Unified Framework for Object Retrieval and Mining
Author :
Anjulan, Arasanathan ; Canagarajah, Nishan
Author_Institution :
BT Res., Ipswich
Abstract :
This paper describes a unified framework for object mining system for videos, which combines shot segmentation, clustering, retrieval and object mining using a single set of detected local invariant regions. The local invariant regions are tracked throughout a shot and stable tracks are extracted. The conventional key frame method is replaced with these stable tracks of local regions to characterize different shots. A grouping technique is introduced to combine the stable tracks into meaningful object clusters. These clusters are used to mine similar objects. Compared to other object mining systems, our approach mines more instances of similar objects in different shots. The proposed framework is applied to full length feature films and the results are compared with state of the art methods.
Keywords :
data mining; feature extraction; image segmentation; pattern clustering; video retrieval; clustering; feature extraction; local invariant regions; object clusters; object retrieval; scene matching; video object mining; video segmentation; Feature extraction; object retrieval; scene matching; video object mining; video segmentation;
Journal_Title :
Circuits and Systems for Video Technology, IEEE Transactions on
DOI :
10.1109/TCSVT.2008.2005801