Objects that undergo non-rigid deformation are common in the real world. A
typical and challenging example is the human faces...
While various techniques
have been developed for deformable shape registration and classification,
benchmarks with detailed labels and landmarks suitable for evaluating such
techniques are still limited. In this paper, we present a novel facial dynamic
dataset HDFD which addresses the gap of existing datasets, including 4D funny
faces with substantial non-isometric deformation, and 4D visual-audio faces of
spoken phrases in a minority language (Welsh). Both datasets are captured from
21 participants. The sequences are manually landmarked, with the spoken phrases
further rated by a Welsh expert for level of fluency. These are useful for
quantitative evaluation of both registration and classification tasks. We
further develop a methodology to evaluate several recent non-rigid surface
registration techniques, using our dynamic sequences as test cases. The study
demonstrates the significance and usefulness of our new dataset --- a
challenging benchmark dataset for future techniques.