Name
Abstract | ||
|---|---|---|
Person re-identification through a camera network deals with finding a correct link between consecutive observations of the same target among different cameras in order to choose the most probable correspondence among a set of possible matches. This task is particularly challenging in presence of low-resolution camera networks. In this work, a method for people re-identification in a framework of low-resolution camera network is presented. The proposed approach can be divided in two parts. First, the illumination changes of a target while crossing the network is analyzed. The color structure is evaluated using a novel color descriptor, the Color Structure Descriptor, which describes the differences of dominant colors between two regions of interest. Afterwards, a new pruning system for the links, the Target Color Structure is proposed. Results shows that the improvements achieved applying Target Color Structure control are up to 4% for the top rank and up to 16% considering the first eleven more similar candidates. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1117/12.2004470 | IMAGE PROCESSING: ALGORITHMS AND SYSTEMS XI |
Keywords | Field | DocType |
Video Surveillance, Person Identification, Context, Histograms, Image color analysis | Histogram,Computer vision,Computer science,Optics,Camera network,Artificial intelligence,Color normalization | Conference |
Volume | ISSN | Citations |
8655 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Federica Battisti | 1 | 293 | 25.35 |
| Marco Carli | 2 | 252 | 28.85 |
| giovanna farinella | 3 | 0 | 0.34 |
| A Neri | 4 | 679 | 72.31 |