Real time facial expression recognition using a novel method
This work addresses the problem of enabling near real-time, invariant facial expression analysis for human-computer interaction, but it is incremental in nature.
The paper tackled real-time facial expression recognition from live webcam feeds, achieving a processing time of 100-120 ms per 10 frames with an accuracy of around 60%.
This paper discusses a novel method for Facial Expression Recognition System which performs facial expression analysis in a near real time from a live web cam feed. Primary objectives were to get results in a near real time with light invariant, person independent and pose invariant way. The system is composed of two different entities trainer and evaluator. Each frame of video feed is passed through a series of steps including haar classifiers, skin detection, feature extraction, feature points tracking, creating a learned Support Vector Machine model to classify emotions to achieve a tradeoff between accuracy and result rate. A processing time of 100-120 ms per 10 frames was achieved with accuracy of around 60%. We measure our accuracy in terms of variety of interaction and classification scenarios. We conclude by discussing relevance of our work to human computer interaction and exploring further measures that can be taken.