Purdue RVL-SLLL ASL database for automatic recognition of American Sign Language

This article reports on an extensive database of American Sign Language (ASL) motions, handshapes, words and sentences. Research on automatic recognition of ASL requires a suitable database for the training and the testing of algorithms. The databases that are currently available do not allow for algorithmic development that requires a step-by-step approach to ASL recognition-from the recognition of individual handshapes, to the recognition of motion primitives, and finally, to the recognition of full sentences. We have sought to remove these deficiencies in a new database-the Purdue RVL-SLLL ASL database.