Title :
Video Google: a text retrieval approach to object matching in videos
Author :
Sivic, Josef ; Zisserman, Andrew
Author_Institution :
Dept. of Eng. Sci., Oxford Univ., UK
Abstract :
We describe an approach to object and scene retrieval which searches for and localizes all the occurrences of a user outlined object in a video. The object is represented by a set of viewpoint invariant region descriptors so that recognition can proceed successfully despite changes in viewpoint, illumination and partial occlusion. The temporal continuity of the video within a shot is used to track the regions in order to reject unstable regions and reduce the effects of noise in the descriptors. The analogy with text retrieval is in the implementation where matches on descriptors are pre-computed (using vector quantization), and inverted file systems and document rankings are used. The result is that retrieved is immediate, returning a ranked list of key frames/shots in the manner of Google. The method is illustrated for matching in two full length feature films.
Keywords :
computer vision; content-based retrieval; image matching; image representation; video signal processing; visual databases; Video Google; document rankings; invariant region descriptors; inverted file systems; noise reduction; object matching; object retrieval; partial occlusion; scene retrieval; text retrieval approach; unstable regions; vector quantization; File systems; Image databases; Layout; Lighting; Noise reduction; Object recognition; Robots; Vector quantization; Visual databases; Web pages;
Conference_Titel :
Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on
Conference_Location :
Nice, France
Print_ISBN :
0-7695-1950-4
DOI :
10.1109/ICCV.2003.1238663