Using latent features for short-term person re-identification with RGB-D cameras

Abstract

This paper presents a system for people re-identification in uncontrolled scenarios using RGB-depth cameras. Compared to conventional RGB cameras, the use of depth information greatly simplifies the tasks of segmentation and tracking. In a previous work, we proposed a similar architecture where people were characterized using colorbased descriptors that we named bodyprints. In this work, we propose the use of latent feature models to extract more relevant information from the bodyprint descriptors by reducing their dimensionality. Latent features can also cope with missing data in case of occlusions. Different probabilistic latent feature models, such as Probabilistic Principal Component Analysis and Factor Analysis, are compared in the paper. The main difference between the models is how the observation noise is handled in each case. Re-identification experiments have been conducted in a real store where people behaved naturally. The results show that the use of the latent features significantly improves the re-identification rates compared to state-of-the-art works.

Histogram of the node strength and histogram of the edge weight: two new features for RGB-D person re-identification

“…Thus, we do not compare our features with these features. We compare our features with two the RGB-D appearancebased features of Eigen-depth [31], latent features [30] and also with SDALF [7], eBiCOV [8] and eSDCknn [10] methods. For this reason, we combine all the methods with skeleton features using the score-level fusion.…”

“…In [29], a texture-based signature named Skeleton-based Person Signature (SPS) including local descriptors around the joint positions of the skeleton of the Kinect sensor was proposed for more robust person re-identification in the presence of strong illumination changes. In [30], the bodyprints were extracted from height maps in which the pixel values represent the height with respect to the ground. The key idea of bodyprints is that each of their elements summarizes the color appearance at a different height.…”