Soft-biometrics evaluation for people re-identification in uncontrolled multi-camera environments

Daniela Moctezuma,Enrique Cabello,Isaac Martín De Diego,Cristina Conde

doi:10.1186/s13640-015-0078-1

Daniela Moctezuma, Enrique Cabello + Show 2 more

Open Access

https://doi.org/10.1186/s13640-015-0078-1

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Abstract

A novel method for person identification based on soft-biometrics and oriented to work in real video surveillance environments is proposed in this paper. Thus, an evaluation of relevance’s level of several appearance features is carried out with this purpose. First, a bag-of-soft-biometric features related to color, texture, local features, and geometry are extracted from individuals. The relevance of each feature has been deeply analyzed through different proposed methods. Features are ranked and weighted according to their relevance value. Later, each method is evaluated under two different scenarios: mono-camera and multi-camera surveillance images. In order to test the system in a realistic way, it has been evaluated over standard databases in the surveillance community: PETS 2006, PETS 2009, CAVIAR, SAIVT-SoftBio, and CAVIAR4REID. Moreover, a new database was acquired at Adolfo Suarez Madrid-Barajas international airport. This database was acquired under regular conditions and infrastructure of the Barajas airport, no additional camera or special settings were installed for this purpose. An analysis of relevance for each feature acquired in these two scenarios is presented. The results obtained demonstrate the promising potential of the soft-biometric approach. Finally, an optimal system configuration according to each scenario is obtained.

Highlights

For many areas of current society, re-identification of human beings based on their biometric or soft-biometric features is becoming an important task
In order to generate an exhaustive evaluation of soft-biometric features, the experiments were conducted using standard databases well-known in the surveillance community (PETS 2006, PETS 2009, CAVIAR, SAIVT-SoftBio, and CAVIAR4REID)
The experiments are conducted in the Southampton multi-biometric tunnel database, and the results show that the use of soft-biometrics is able to improve the performance of recognition

Summary

Introduction

For many areas of current society, re-identification of human beings based on their biometric or soft-biometric features is becoming an important task. Person re-identification is about identifying a specific individual across non-overlapping distributed cameras at different times and locations. This task is challenging due to the dramatic changes in an individual’s appearance, in terms of lighting, occlusion, pose, zoom, and camera quality, among others [1]. The soft-biometric features are not intrusive during the acquisition process and can be applied directly in most of the existing camera systems For these reasons, they can be considered as a promising approach. This work proposes an identification system that can identify N pre-specified individuals, while rejecting everybody else This approach would be useful for intelligent video-surveillance, where the N individuals would be the suspects in the watch-list. The results show the huge potential of soft-biometric features

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Conclusion