Title :
A Novel Semantic Video Classification Model
Author :
Ren, Wei ; Singh, Maneesha ; Singh, Sameer
Author_Institution :
Fac. of Comput. & Inf. Eng., Peking Univ., Shenzhen
Abstract :
In this paper, we propose a novel spatio-temporal video retrieval model to extract spatio-temporal attributes for semantic video category classification using high-level reasoning of video objects and scenes. We also explore the semantic logical inference learning of video attributes based on interpreting camera movements and object spatial constraints, as well the views on temporal continuity of video. We have used Minerva international video benchmark for the analysis of our algorithm.
Keywords :
image classification; image motion analysis; inference mechanisms; learning (artificial intelligence); video retrieval; Minerva international video benchmark; camera movement; high-level reasoning; semantic logical inference learning; semantic video classification model; spatio-temporal video retrieval model; Application software; Data mining; Image processing; Image retrieval; Indexing; Information retrieval; Layout; Video compression; Video sequences; Videoconference; Binary strings; Spatial video retrieval; Spatio-temporal video retrieval; Temporal video retrieval; video classification;
Conference_Titel :
Image Processing Theory, Tools and Applications, 2008. IPTA 2008. First Workshops on
Conference_Location :
Sousse
Print_ISBN :
978-1-4244-3321-6
Electronic_ISBN :
978-1-4244-3322-3
DOI :
10.1109/IPTA.2008.4743749