Vision-based recognition of fingerspelled acronyms using hierarchical temporal memory

Abstract

In this paper, a new, glove-free method for recognition of fingerspelled acronyms using hierarchical temporal memory has been proposed. The task is challenging because many signs look similar from the camera viewpoint. Moreover handshapes are distorted strongly as a result of coarticulation and motion blur, especially in the fluent fingerspelling. In the described work, the problem has been tackled by applying the new, bio-inspired recognition engine, based on structural and functional properties of mammalian neocortex, robust to local changes shape descriptors, and a training scheme allowing for capture possible handshape deformations in a manner that is lexicon independent. © 2012 Springer-Verlag Berlin Heidelberg.