Researches

Human Pose Estimation

As a fundamental research topic in computer vision, Human Pose Estimation (HPE) aims to locate key points on human body on images or in 3D space, which plays an important role in behavior understanding. Compared to 2D pose estimation which locates key points only on images, 3D pose estimation produces 3D key point locations in 3D space, leading to a wider application. So far, 3D Human pose estimation has become a comprehensive research topic based on machine learning, projective geometry, optimization, etc.

We aim to precisely attain 3D coordinates of human body key points from multi-view images. On the basis of common methods in visual pose estimation like deep learning and epipolar geometry, we are seeking the practical pathway to aid 3D HPE using anatomical priors, IMU, dynamics, etc. We also pay special attention to pose estimation under binocular, especially short-baselined camera settings, and the implementations of research finding in the form of projects.