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| Content Provider | Springer Nature Link |
|---|---|
| Author | Chandrasekhar, Vijay Takacs, Gabriel Chen, David M. Tsai, Sam S. Reznik, Yuriy Grzeszczuk, Radek Girod, Bernd |
| Copyright Year | 2011 |
| Abstract | Establishing visual correspondences is an essential component of many computer vision problems, which is often done with local feature-descriptors. Transmission and storage of these descriptors are of critical importance in the context of mobile visual search applications. We propose a framework for computing low bit-rate feature descriptors with a 20× reduction in bit rate compared to state-of-the-art descriptors. The framework offers low complexity and has significant speed-up in the matching stage. We show how to efficiently compute distances between descriptors in the compressed domain eliminating the need for decoding. We perform a comprehensive performance comparison with SIFT, SURF, BRIEF, MPEG-7 image signatures and other low bit-rate descriptors and show that our proposed CHoG descriptor outperforms existing schemes significantly over a wide range of bitrates. We implement the descriptor in a mobile image retrieval system and for a database of 1 million CD, DVD and book covers, we achieve 96% retrieval accuracy using only 4 KB of data per query image. |
| Starting Page | 384 |
| Ending Page | 399 |
| Page Count | 16 |
| File Format | |
| ISSN | 09205691 |
| Journal | International Journal of Computer Vision |
| Volume Number | 96 |
| Issue Number | 3 |
| e-ISSN | 15731405 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2011-05-15 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | CHoG Feature descriptor Mobile visual search Content-based image retrieval Histogram-of-gradients Low bitrate Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence (incl. Robotics) Pattern Recognition Image Processing and Computer Vision |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Computer Vision and Pattern Recognition Software |
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