Front view vs. side view of facial and postural expressions of emotions in a virtual character
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Simple cartoon facial expressions can be represented by emoticons, that is, a special sequence of symbols. This inspires us that a sketch of facial feature contour may be adequate to recognize expressions. Metrics of such sketches are easier to be calibrated under varying illumination and head pose. While skin wrinkles such as nasolabial folds, eye pouches, dimples, forehead, and chin furrows are not salient facial features, they may convey crucial subtle signals about an individual's emotion. Our experiments have shown that the side-view profile plus skin wrinkles can correctly differentiate nearly 70% expressions, and it contributes to the increase of overall recognition rate. Finally, we compare the accuracy and robustness of various local and global processing schemes, especially under the condition of partial occlusion.