Name
Abstract | ||
|---|---|---|
In many multi-camera surveillance systems, there is a need to identify whether a captured person have emerged before over the network of cameras. This is the person re-identification problem. In this paper, we propose a novel re-identification method based on super pixel feature. Firstly, local C-SIFT features based on super pixel are extracted as visual words, and appearance details are used to describe detecting objects. Secondly, a TF-IDF vocabulary index tree is built to speed up person search. Finally, an image-retrieval way is adopted to implement person re-identification. Experimental results on ETHZ dataset show that our method is better than the approach proposed by Schwartz et.al and two machine learning methods based on SVM and PCA. © Springer-Verlag 2013. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-35725-1_18 | MMM |
Keywords | Field | DocType |
person re-identification,super pixel,visual word,vocabulary tree | Computer vision,Pattern recognition,Computer science,Vocabulary tree,Support vector machine,Pixel,Artificial intelligence,Feature based,Vocabulary,Speedup,Visual Word | Conference |
Volume | Issue | ISSN |
7732 LNCS | PART 1 | 16113349 |
Citations | PageRank | References |
0 | 0.34 | 15 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cheng Liu | 1 | 3 | 3.42 |
| Zhicheng Zhao | 2 | 29 | 11.69 |