The Next Generation of Facial Expression Recognition Systems (Michel Valstar: Oct 18)

The previous decade has seen a large number of publications on Automatic Facial Expression Recognition systems (AFERS). Also, recently the first AFERS programmes have been made available, either publicly by academics, or for sale by companies, making it clear for everyone what works and what doesn't. The first facial expression recognition challenge (FERA2011) further serves to shed a light on the efforts in this field, comparing many state of the art approaches on the same challenging dataset. What we now see is the advent of a second generation of AFERS. Building upon the successes of the first generation, these new systems attempt to tackle all the open challenges in this field by combining different approaches, as well as integrating sources of information other than the face (e.g. head actions). He described two recent developments towards such a second generation of AFERS, to wit the novel facial point detection algorithm Local Evidence Aggregation Regressors (LEAR) and a novel dynamic appearance descriptor called LPQ-TOP.