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regional histograms) represents the best strategy to
identify pedestrians in a multi-camera context.
6 CONCLUSIONS AND FUTURE
WORKS
In this paper, we have introduced a new regional
color histograms feature vector to characterize a per-
son which is integrated into an extensive comparative
study between different existing descriptors based on
color, texture and shape information applied to peo-
ple re-identification and tracking in multi-camera. To
ensure this objective, two separate tests have been
performed. The first one consists in evaluating the
performances of already introduced feature vectors in
terms of people re-identification as CMC curves on
VIPER pedestrians dataset. The second test, that is
more generic, allows us to evaluate simultaneously
the discriminatory power of these descriptors in terms
of persons tracking and re-identification.
Given the complexity of the multi-camera pedes-
trians re-identification and the number of constraints
to manage, a new approach based on a fusion of de-
scriptors selected from two performed comparative
studies is presented in this paper. Two variants of the
proposed approach (cascade of color descriptors and
cascade of color and texture descriptors) are tested
and compared with several existing approaches. Ex-
perimental results show that the proposed color-based
approach provides very satisfactory performances de-
spite the highly articulated human body, lighting con-
ditions changes and large pose variations.
Future work will focus on developing a robust
behavioral analysis module and merging it with the
proposed cascade of color descriptors to improve the
multi-camera people tracking and identification per-
formances.
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