Search Results for author: Hung-Min Hsu

Found 7 papers, 0 papers with code

GaitTAKE: Gait Recognition by Temporal Attention and Keypoint-guided Embedding

no code implementations7 Jul 2022 Hung-Min Hsu, Yizhou Wang, Cheng-Yen Yang, Jenq-Neng Hwang, Hoang Le Uyen Thuc, Kwang-Ju Kim

Gait recognition, which refers to the recognition or identification of a person based on their body shape and walking styles, derived from video data captured from a distance, is widely used in crime prevention, forensic identification, and social security.

Gait Recognition

Package Theft Detection from Smart Home Security Cameras

no code implementations24 May 2022 Hung-Min Hsu, Xinyu Yuan, Baohua Zhu, Zhongwei Cheng, Lin Chen

Package theft detection has been a challenging task mainly due to lack of training data and a wide variety of package theft cases in reality.

Multi-Target Multi-Camera Tracking of Vehicles using Metadata-Aided Re-ID and Trajectory-Based Camera Link Model

no code implementations3 May 2021 Hung-Min Hsu, Jiarui Cai, Yizhou Wang, Jenq-Neng Hwang, Kwang-Ju Kim

In this paper, we propose a novel framework for multi-target multi-camera tracking (MTMCT) of vehicles based on metadata-aided re-identification (MA-ReID) and the trajectory-based camera link model (TCLM).

Clustering

Traffic-Aware Multi-Camera Tracking of Vehicles Based on ReID and Camera Link Model

no code implementations22 Aug 2020 Hung-Min Hsu, Yizhou Wang, Jenq-Neng Hwang

In this paper, we propose an effective and reliable MTMCT framework for vehicles, which consists of a traffic-aware single camera tracking (TSCT) algorithm, a trajectory-based camera link model (CLM) for vehicle re-identification (ReID), and a hierarchical clustering algorithm to obtain the cross camera vehicle trajectories.

Clustering Vehicle Re-Identification

IA-MOT: Instance-Aware Multi-Object Tracking with Motion Consistency

no code implementations24 Jun 2020 Jiarui Cai, Yizhou Wang, Haotian Zhang, Hung-Min Hsu, Chengqian Ma, Jenq-Neng Hwang

Meanwhile, the spatial attention, which focuses on the foreground within the bounding boxes, is generated from the given instance masks and applied to the extracted embedding features.

Multi-Object Tracking Multiple Object Tracking +1

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