We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...
This paper proposes a learnt data-driven approach for accurate, real-time tracking of facial features using only intensity information. Constraints such as a-priori shape models o...
Eng-Jon Ong, Yuxuan Lan, Barry Theobald, Richard H...
This paper presents a robust and accurate method for joint head pose and facial actions tracking, even under challenging conditions such as varying lighting, large head movements,...
This paper addresses the 3D tracking of pose and animation of the human face in monocular image sequences using Active Appearance Models. The classical appearancebased tracking su...
Face detection and tracking, through image sequences, are primary steps in many applications such as video surveillance, human computer interface, and expression analysis. Many cu...