Abstract
This work explores different types of multi-shot descriptors for re-identification in an on-the-fly enrolled environment using RGB-D sensors. We present a full re-identification pipeline complete with detection, segmentation, feature extraction, and re-identification, which expands on previous work by using multi-shot descriptors modeling people over a full camera pass instead of single frames with no temporal linking. We compare two different multi-shot models; mean histogram and histogram series, and test them each in 3 different color spaces. Both histogram descriptors are assisted by a depth-based pruning step where unlikely candidates are filtered away. Tests are run on 3 sequences captured in different circumstances and lighting situations to ensure proper generalization and lighting/environment invariance.
Originalsprog | Engelsk |
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Titel | Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) |
Redaktører | José Braz, Sebastiano Battiato, Francisco Imai |
Vol/bind | 2 |
Forlag | SciTePress |
Publikationsdato | 2015 |
Sider | 244-251 |
ISBN (Trykt) | 978-989-758-090-1 |
DOI | |
Status | Udgivet - 2015 |
Begivenhed | International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications 2015 - Berlin, Tyskland Varighed: 11 mar. 2015 → 14 mar. 2015 Konferencens nummer: 11 |
Konference
Konference | International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications 2015 |
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Nummer | 11 |
Land/Område | Tyskland |
By | Berlin |
Periode | 11/03/2015 → 14/03/2015 |