Authors:
Athira Nambiar
;
Alexandre Bernardino
and
Jacinto C. Nascimento
Affiliation:
Instituto Superior Técnico, Portugal
Keyword(s):
Soft biometrics, Shape Context, SVM Regression, Re-identification, Silhouettes, Retrieval, Surveillance.
Abstract:
We propose a novel methodology for person re-identification (Re-ID) based on the biometric description of
the upper-torso region of the human body. The proposed methodology leverages soft biometrics via Support
Vector Regression (SVR) and Shape Context (SC) features obtained from the upper-torso silhouette of the
human body. First, mappings from the upper-torso Shape Context to soft biometrics are learned from virtual
avatars rendered by computer graphics engines, to circumvent the need for time consuming manual labelling
of human datasets. Second, it is possible to formulate a human query of a given suspect against a gallery of
previously stored soft biometrics. At this point, the proposed system is able to provide a ranked list of the
persons, based on the description given. Third, an extensive study on the different regression methodologies
to achieve the above mentioned mappings is carried out. We also conduct real time Re-ID experiments in an
existing Re-ID dataset, and promisin
g results are reported.
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