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FACIAL EXPRESSION RECOGNITION USING RELATIONS DETERMINED BY CLASS-TO-CLASS COMPARISONS
FACIAL EXPRESSION RECOGNITION USING RELATIONS DETERMINED BY CLASS-TO-CLASS COMPARISONS
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机译:使用类间比较确定的关系进行面部表情识别
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摘要
Facial expressions are recognized using relations determined by class-to-class comparisons. In one example, descriptors are determined for each of a plurality of facial expression classes. Pair-wise facial expression class-to-class tasks are defined. A set of discriminative image patches are learned for each task using labelled training images. Each image patch is a portion of an image. Differences in the learned image patches in each training image are determined for each task. A relation graph is defined for each image for each task using the differences. A final descriptor is determined for each image by stacking and concatenating the relation graphs for each task. Finally, the final descriptors of the images of the are fed into a training algorithm to learn a final facial expression model.
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