Facial emotions and expressive facial motions have become an intrinsic part of many graphics systems and human computer interaction applications. The dynamics and high dimensionality of facial motion data make its exploration and processing challenging. In this paper, we propose a novel visualization system for expressive facial motion data exploration. Based on Principal Component Analysis (PCA) dimensionality reduction on anatomical facial sub regions, high dimensional facial motion data is mapped to 3D spaces. We further rendered it as colored 3D trajectories and color represents different emotion. We design an intuitive interface to allow users effectively explore and analyze high dimensional facial motion spaces. The applications of our visualization system on novel facial motion synthesis and emotion recognition are demonstrated.

This paper presents a technique to reconstruct a 3D human face from a single shaded face image. The core idea of this work is to find a possible relationship between an image subspace and a 3D subspace. In this work, the subspaces are created by Principle Component Analysis to only capture the major factors for creating a face in each subspace. The subspaces are then adjusted to arrange them in a comparable range. By inputting a novel 2D shading face image, a subspace crossing engine developed for this work will estimate the major factors of the 2D shading face image creation and use them to compose a 3D shape automatically. The evaluation reveals that the researchers approach reconstructed 3D faces faster and closer to the 3D ground-truth faces than a traditional approach in a controlled environment.

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This paper describes a practical technique for 3D artistic face modeling where a human identity can be inserted into a 3D artistic face. This approach can automatically extract the human identity from a 3D human face model and then transfer it to a 3D artistic face model in a controllable manner. Its core idea is to construct a face geometry space and a face texture space based on a precollected 3D face dataset. Then, these spaces are used to extract and blend the face models together based on their facial identities and styles. This approach can enable a novice user to interactively generate various artistic faces quickly using a slider control. Also, it can run in real-time on an off-the-shelf computer without GPU acceleration. This approach can be broadly used in various 3D artistic face modeling applications such as a rapid creation of a cartoon crowd with different cartoon characters.

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