A method to infer emotions from facial Action Units

We present a robust method to map detected facial Action Units (AUs) to six basic emotions. Automatic AU recognition is prone to errors due to illumination, tracking failures and occlusions. Hence, traditional rule based methods to map AUs to emotions are very sensitive to false positives and misses among the AUs. In our method, a set of chosen AUs are mapped to the six basic emotions using a learned statistical relationship and a suitable matching technique. Relationships between the AUs and emotions are captured as template strings comprising the most discriminative AUs for each emotion. The template strings are computed using a concept called discriminative power. The Longest Common Subsequence (LCS) distance, an approach for approximate string matching, is applied to calculate the closeness of a test string of AUs with the template strings, and hence infer the underlying emotions. LCS is found to be efficient in handling practical issues like erroneous AU detection and helps to r...

• Type: Journal
• Year: 2011
• Where: ICASSP
• Authors: Sudha Velusamy, Hariprasad Kannan, Balasubramanian Anand, Anshul Sharma, Bilva Navathe
• Keywords: Basic Emotions, Discriminative Aus, ICASSP 2011, Signal Processing, Template Strings