Name
Abstract | ||
|---|---|---|
State-of-the-art image retrieval pipelines are based on "bag-of-words" matching. We note that the original order in which features are extracted from the image is discarded in the "bag-of-words" matching pipeline. As a result, a set of features extracted from a query image can be transmitted in any order. A set of m unique features has m ! orderings, and if the order of transmission can be discarded, one can reduce the query size by an additional log(2) (m !) bits. We propose a coding scheme based on Digital Search Trees that reduces size of a set of features by approximately log(2)(m !) bits. We perform analysis of the scheme, and show how it applies to any set of symbols in which order can be discarded. We illustrate how the scheme can be applied to a set of low bitrate Compressed Histogram of Gradients (CHoG) descriptors. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICCVW.2011.6130219 | 2011 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCV WORKSHOPS) |
Keywords | Field | DocType |
feature extraction,image retrieval,indexes,indexation,bag of words,silicon | Pipeline transport,Automatic image annotation,Feature detection (computer vision),Pattern recognition,Image matching,Computer science,Image retrieval,Coding (social sciences),Histogram of oriented gradients,Artificial intelligence,Visual Word | Conference |
Volume | Issue | Citations |
2011 | 1 | 5 |
PageRank | References | Authors |
0.52 | 13 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vijay Chandrasekhar | 1 | 949 | 45.35 |
| yuriy a reznik | 2 | 258 | 25.70 |
| Gabriel Takacs | 3 | 698 | 31.40 |
| David M. Chen | 4 | 947 | 42.62 |
| Sam S. Tsai | 5 | 724 | 36.51 |
| Radek Grzeszczuk | 6 | 2562 | 204.55 |
| Bernd Girod | 7 | 8988 | 1062.96 |