In this paper, we propose an embedding method to seek an optimal low-dimensional manifold describing the intrinsical pose variations and to provide an identity-independent head pos...
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
A variety of digital watermarking applications have emerged recently that require the design of systems for embedding one signal (the "embedded signal" or "watermar...
The locally linear embedding (LLE) algorithm is considered as a powerful method for the problem of nonlinear dimensionality reduction. In this paper, first, a new method called cl...
This paper proposes a method for key-frame selection of captured motion data. In many cases, it is desirable to obtain a compact representation of the human motion. Key-framing is...