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Using video objects and relevance feedback in video retrieval

Sav, Sorin Vasile and Lee, Hyowon and Smeaton, Alan F. and O'Connor, Noel E. and Murphy, Noel (2005) Using video objects and relevance feedback in video retrieval. In: SPIE Optics East 2005 - Internet Multimedia Management Systems VI, 23-26 October 2005, Boston, MA, USA.

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Video retrieval is mostly based on using text from dialogue and this remains the most signi¯cant component, despite progress in other aspects. One problem with this is when a searcher wants to locate video based on what is appearing in the video rather than what is being spoken about. Alternatives such as automatically-detected features and image-based keyframe matching can be used, though these still need further improvement in quality. One other modality for video retrieval is based on segmenting objects from video and allowing end users to use these as part of querying. This uses similarity between query objects and objects from video, and in theory allows retrieval based on what is actually appearing on-screen. The main hurdles to greater use of this are the overhead of object segmentation on large amounts of video and the issue of whether we can actually achieve effective object-based retrieval. We describe a system to support object-based video retrieval where a user selects example video objects as part of the query. During a search a user builds up a set of these which are matched against objects previously segmented from a video library. This match is based on MPEG-7 Dominant Colour, Shape Compaction and Texture Browsing descriptors. We use a user-driven semi-automated segmentation process to segment the video archive which is very accurate and is faster than conventional video annotation.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:Video retrieval; shot retrieval; object segmentation; object retrieval;
Subjects:Computer Science > Digital video
Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Research Initiatives and Centres > Adaptive Information Cluster (AIC)
Publisher:Optical Society of America
Official URL:
Copyright Information:Copyright 2005 Society of Photo-Optical Instrumentation Engineers. This paper was published in Multimedia Systems and Applications VIII (Proceedings Volume) - Proceedings of SPIE Volume: 6015 and is made available as an electronic reprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Funders:Science Foundation Ireland, SFI 03/IN.3/I361, Enterprise Ireland
ID Code:338
Deposited On:13 Mar 2008 by DORAS Administrator. Last Modified 17 Oct 2016 15:16

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