Human 3D Pose Estimation From Videos: Challenges and Solutions

Описание к видео Human 3D Pose Estimation From Videos: Challenges and Solutions

Presented by SGInnovate and NUS Centre for Research in Privacy Technologies (N-CRiPT)

With the ubiquitous presence of cameras (e.g. CCTV cameras, mobile phones, etc.), there has been an explosion of images and video data. While these visual data presents advantages and conveniences, they come with a cost: potential breach of privacy and confidentiality, particularly for information related to human poses and actions. In this event, Associate Professor Robby T. Tan will focus on the technical challenges and the possible solutions to predict human 3D poses from a monocular video.

For an in-depth look into the session, Associate Prof Tan will discuss some existing top-down and bottom-up approaches of human 3D pose estimation and explain in detail the problems when occlusions happen or when the ground-truth 3D data is insufficient to capture all possible poses. He will also share NCRIPT's solutions for these two crucial scenarios. By the end of the event, you will walk away with an understanding of the state of the art technologies that are ready to be utilised to analyse privacy information in videos related to human actions and poses.

Date: 12 May 2021, Wednesday
Time: 11:00am - 12:00pm (Singapore Time / UTC +8)

Programme:
11:00am - 11:05am: Introduction and Welcome by SGInnovate
11:05am - 11:40pm: Presentation on Human 3D Pose Estimation From Videos: Challenges and Solutions by Associate Professor Robby T. Tan
11:40am - 12:00pm: Fireside Chat and Q&A Session with:

Associate Professor Robby T. Tan, Associate Professor, Yale-NUS College and Department of Electrical and Computing Engineering, National University of Singapore
Moderator: Dr Jithin Vachery, Postdoctoral Research Fellow, School of Computing, National University of Singapore

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