Real-time emotion recognition for gaming using deep convolutional network features
نویسنده
چکیده
The goal of the present study is to explore the application of deep convolutional network features to emotion recognition. Results indicate that they perform similarly to recently published models at a best recognition rate of 94.4%, and do so with a single still image rather than a video stream. An implementation of an affective feedback game is also described, where a classifier using these features tracks the facial expressions of a player in real-time. Keywords—emotion recognition, convolutional network, affective computing
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ورودعنوان ژورنال:
- CoRR
دوره abs/1408.3750 شماره
صفحات -
تاریخ انتشار 2014