We performed an electronic database search of published works from 2012 to mid-2021 that
focus on human gait studies and apply machine learning techniques. We identified six key …

Abstract Person Re-Identification (Re-ID) is a critical aspect of visual surveillance systems,
which aims to automatically recognize and locate individuals across a multi-camera network …

We propose a new bottom-up method for multi-person 2D human pose estimation that is
particularly well suited for urban mobility such as self-driving cars and delivery robots. The …

Pedestrian misalignment, which mainly arises from detector errors and pose variations, is a
critical problem for a robust person re-identification (re-ID) system. With poor alignment, the …

Variations in visual factors such as viewpoint, pose, illumination and background, are
usually viewed as important challenges in person re-identification (re-ID). In spite of …

Person re-identification is an important task in video surveillance systems. It can be formally
defined as establishing the correspondence between images of a person taken from …

Person re-identification (re-id) is a critical problem in video analytics applications such as
security and surveillance. The public release of several datasets and code for vision …

Due to domain bias, directly deploying a deep person re-identification (re-ID) model trained
on one dataset often achieves considerably poor accuracy on another dataset. In this article …

Most existing person re-identification (re-id) models focus on matching still person images
across disjoint camera views using the setting of either single-shot or multi-shot. Since …

Person re-identification (Re-ID) is an important problem in video surveillance for matching
pedestrian images across non-overlap** camera views. Currently, most works focus on …