Online Multiple Object Tracking based on Joint-Detection-and-Embedding Network

ROAR of SUTD, IEEE Signal Processing Singapore Chapter, IEEE Circuits and Systems Singapore Chapter and TDSS hosted an online seminar by Dr. Zhenyu Weng.

Speaker: Dr Zhenyu Weng, School of EEE, Nanyang Technological University, Singapore

Jointly organized by
Robotics & Automation Research Lab (ROAR), Singapore University of Technology and Design
IEEE Signal Processing Singapore Chapter
IEEE Circuits and Systems Singapore Chapter
Teochew Doctorate Society, Singapore

Date and Time: 1 June 2021, Tuesday, 3 – 4pm

Abstract:
Most of online multiple object tracking methods consist of two subtasks, detection and embedding, and thus they need two different networks. To reduce the complexity, recent methods for tracking persons integrate these two subtasks into a unified network. In this talk, we cover two topics. Firstly, different from the above methods focusing on designing networks, we explore the online association strategy to better associate the tracks with the detected objects after performing detection and extracting embedding features from the detected objects. Secondly, we propose a unified network for face detection and embedding, and then use the proposed association strategy for multiple face tracking.

Bio:
Zhenyu Weng received the B.S. degree in Computer Science and Technology at Sun Yat-sen University, China and the Ph.D. degree from School of Electronics Engineering and Computer Science at Peking University, China. He is currently working as a research fellow in School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. His research interests cover machine learning, computer vision, deep learning, and incremental learning.