PhD Thesis Proposal - Haidong Zhu

Title: Body Shape Reconstruction for Video-based Person Identification

Committee: Ram Nevatia (Chair), Ulrich Neumann, Mohammad Soleymani, Stefanos Nikolaidis, Antonio Ortega

Date: Monday April 17, 2pm PST

Abstract: The recognition of individuals in videos is a crucial task in connecting video clips of the same person captured by multiple non-overlapping cameras. While image-based person identification mainly relies on the person's appearance, video-based identification can exploit additional external information, such as walking poses and general body shape, leading to less biased identification results. However, changes in body shape due to clothing and camera views can negatively impact such biometrics. To address this limitation, we propose reconstructing 3-D human body shapes across frames to provide consistency and invariance to view changes, improving identification accuracy and robustness. Existing 3-D body shape reconstruction methods typically focus on frame-by-frame reconstruction and fail to leverage the consistency between frames. In this proposal, we aim to enhance body shape reconstruction and representation of objects and body. Additionally, we will extend these methods to reconstruct body shapes in videos and utilize this information to aid person identification. Our proposed approach leverages temporal information between frames and utilizes body shape information for identification assistance, with the goal of improving identification accuracy.

Audiences: Everyone Is Invited

Contact: Melissa Ochoa

Event Link: https://usc.zoom.us/j/94346121440?pwd=S3JSVVRpTFc5WFB5THEvWE9TTEhSQT09