Baştan, MuhammetGüdükbay, UğurUlusoy, Özgür2016-02-082016-02-082008-06http://hdl.handle.net/11693/26852Date of Conference: 23-26 June, 2008Conference name: IEEE International Conference on Multimedia and Expo, 2008We describe a method to automatically extract important video objects for object-based indexing. Most of the existing salient object detection approaches detect visually conspicuous structures in images, while our method aims to find regions that may be important for indexing in a video database system. Our method works on a shot basis. We first segment each frame to obtain homogeneous regions in terms of color and texture. Then, we extract a set of regional and inter-regional color, shape, texture and motion features for all regions, which are classified as being important or not using SVMs trained on a few hundreds of example regions. Finally, each important region is tracked within each shot for trajectory generation and consistency check. Experimental results from news video sequences show that the proposed approach is effective. © 2008 IEEE.EnglishImportant objectIndexingSegmentationVideo object extractionDatabase systemsExhibitionsFeature extractionIndexing (of information)Motion compensationMotion estimationPhotographyTexturesVideo recordingConsistency checksHomogeneous regionsImportant objectMotion featuresNews videosSalient object detectionsSegmentationTrajectory generationsVideo database systemsVideo object extractionVideo objectsObject recognitionConference Paper10.1109/ICME.2008.4607695