Content-based attention ranking using visual and contextual attention model for baseball videos
IEEE Transactions on Multimedia - Special issue on integration of context and content
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In this paper, a real-time system to create a talking head from a video sequence without any user intervention is presented. In the proposed system, a probabilistic approach, to decide whether or not extracted facial features are appropriate for creating a three-dimensional (3-D) face model, is presented. Automatically extracted two-dimensional facial features from a video sequence are fed into the proposed probabilistic framework before a corresponding 3-D face model is built to avoid generating an unnatural or nonrealistic 3-D face model. To extract face shape, we also present a face shape extractor based on an ellipse model controlled by three anchor points, which is accurate and computationally cheap. To create a 3-D face model, a least-square approach is presented to find a coefficient vector that is necessary to adapt a generic 3-D model into the extracted facial features. Experimental results show that the proposed system can efficiently build a 3-D face model from a video sequence without any user intervention for various Internet applications including virtual conference and a virtual story teller that do not require much head movements or high-quality facial animation.