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Person re-identification is a challenge in video-based surveillance where the goal is to identify the same person in different camera views. In recent years, many algorithms have been proposed that approach this problem by designing suitable feature representations for images of persons or by training appropriate distance metrics that learn to distinguish between images of different persons. Aggregating...
In spite of recent progress achieved in near-frontal face recognition, the problem of pose variations prevalent in 2D facial images captured in the wild still remains a challenging and unsolved issue. Among existing approaches of pose-invariant face recognition, 3D-aided methods have been demonstrated effective and promising. In this paper, we present an extensive evaluation of two widely adopted...
Asymmetric 3D-2D face recognition (FR) aims to recognize individuals from 2D face images using textured 3D face models in the gallery (or vice versa). This new FR scenario has the potential to be readily deployable in field applications while still keeping the advantages of 3D FR solutions of being more robust to pose and lighting variations. In this paper, we propose a new experimental protocol based...
Illumination alignment is accomplished by relighting or unlighting methods that compensate the appearance differences due to variations in illumination conditions between a pair of face images or among a set of face images. In this paper, we propose a lighting ratio based method that avoids parameter tuning process by using an image-specific low-pass filtering. In addition, it includes an optimization...
In this paper, we address the problem of multiple person re-identification in the absence of calibration data or prior knowledge about the geospatial location of cameras. Multiple person re-identification is a open set matching problem with a dynamically evolving gallery and probe set. We present a part-based spatio-temporal model that learns a person's characteristic appearance as well as it's variations...
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