Mask R-CNN for Ear Detection

Ear detection is an important step in ear recognition pipeline as it makes or breaks the system. However, in the literature there is arguably the lack of ear detection approaches available. This poses a problem for opening ear recognition system to wider use and applications in commercial systems. To tackle this problem we present the use of Mask R-CNN for pixel-wise ear detection. Furthermore, we directly compare our approach to one of the previous best performing pixel-wise ear detection approach by using the same dataset and protocol. Our results with intersection over union score of 79.24% on AWE dataset show the superiority of our approach and present a viable approach for future use in ear recognition pipelines.