Air-writing recognition using reverse time ordered stroke context

A novel real-time recognition system is proposed to recognize finger air-writing characters without using any pen-starting-lift information. It presents a novel reverse time ordered stroke context to represent an air-writing trajectory in a backward way so that redundant starting-lift data can be effectively filtered out. Another two challenging problems often happen in the air-writing recognition system, i.e., the multiplicity problem of writing and the confusion problem. The first one means a character is always written differently and the second one means different various characters own similar writing trajectory. To tackle them, a three-layer hierarchical structure to represent an air-writing character with different sampling rates is proposed. All the alphabets (including lowercase, capital, and digital letters) are recognized in this system. Performance evaluation shows that the proposed solution achieves quite higher recognition accuracy (more than 94.7%) even though no starting gesture is required.