Spatial data structure indexing for video databases
| dc.contributor.author | Xie, Enhai | |
| dc.date.accessioned | 2023-03-01T18:26:50Z | |
| dc.date.available | 2023-03-01T18:26:50Z | |
| dc.date.issued | 2000 | |
| dc.description.abstract | This thesis explores the application of k-d range search data structures to digital video data. Content-based queries based on colour histogram indexing and colour space indexing for MPEG-2 video I-frames are defined and implemented. Experimentation using 100 MPEG-2 video clips comprising 5706 I-frames was carried out. Two spatial data structures (a 4-d tree and a colour space tree) can satisfy queries such as "find MPEG-2 video 1-frames with > t% pixels in colour range [R[subscript L], R[subscript H]]" or "find MPEG-2 video I-frames with > t% pixels in color range [R[subscript L], R[subscript H]], [G[subscript L], G[subscript H]], [B[subscript L], B[subscript H]], simultaneously", respectively. Prototype software was written in C++ on a UNIX system to test both histogram and colour space range search. A 4-d tree containing 5706 I-frames from 100 MPEG-2 video clips was built in 71 seconds. The average histogram range search time was 37 seconds on a Sun Microsystems ULTRA 5 workstation. A colour space tree of 300 I-frames required 5491 seconds to build, and 2 seconds to answer a colour space query on a Sun Microsystems ENTERPRISE 250 workstation. | |
| dc.description.copyright | Copyright @ Enhai Xie, 2000. | |
| dc.identifier.uri | https://unbscholar.lib.unb.ca/handle/1882/14639 | |
| dc.rights | http://purl.org/coar/access_right/c_abf2 | |
| dc.subject.discipline | Computer Science | |
| dc.title | Spatial data structure indexing for video databases | |
| dc.type | technical report |
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