Using Segmented Objects in Ostensive Video Shot Retrieval

• Published in: Adaptive Multimedia Retrieval: User, Context, and Feedback pp. 155 - 167
• Main Authors: Sav, Sorin, Lee, Hyowon, Smeaton, Alan F., O’Connor, Noel E.
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2006; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Artificial intelligence; Computer science; control theory; systems; Exact sciences and technology; Gabor Wavelet; Information systems. Data bases; Knowledge State; Memory organisation. Data processing; Pattern recognition. Digital image processing. Computational geometry; Query Object; Relevance Feedback; Software; Video Object; Multimedia; Checkpointing; Database query; Information system; Image retrieval; Object oriented; Video signal; Information retrieval; Modeling; Texture; Color image
• ISBN: 3540321748; 9783540321743
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/11670834_13

This paper presents a system for video shot retrieval in which shots are retrieved based on matching video objects using a combination of colour, shape and texture. Rather than matching on individual objects, our system supports sets of query objects which in total reflect the user’s object-based information need. Our work also adapts to a shifting user information need by initiating the partitioning of a user’s search into two or more distinct search threads, which can be followed by the user in sequence. This is an automatic process which maps neatly to the ostensive model for information retrieval in that it allows a user to place a virtual checkpoint on their search, explore one thread or aspect of their information need and then return to that checkpoint to then explore an alternative thread. Our system is fully functional and operational and in this paper we illustrate several design decisions we have made in building it.