Abstract
Visual (image and video) database systems require efficient indexing to enable fast access to the images in a database. In addition, the large memory capacity and channel bandwidth requirements for the storage and transmission ofvisual data necessitate the use of compression techniques. Vector quantization (VQ) is an efficient technique for low bit rate image and video compression. In addition, the low complexity of the decoder makes VQ attractive for low power systems and applications which require fast decoding. The detection of camera operations provides a mechanism to segment a long video shot into short clips defined by homogeneous camera operations which can then be used for indexing. In this paper, we present a technique for the detection of camera operations in video sequences compressed using VQ. The proposed technique is executed in the compressed domain. This entails significant savings in computational and storage costs resulting in faster execution.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 493-505 |
| Number of pages | 13 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 3022 |
| DOIs | |
| State | Published - Jan 15 1997 |
| Externally published | Yes |
| Event | Storage and Retrieval for Image and Video Databases V 1997 - San Jose, United States Duration: Feb 8 1997 → Feb 14 1997 |
Keywords
- Camera operations
- Vector quantization
- Video indexing
- Video segmentation
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering