Real-Time Implementation of Time-Space Continuous Dynamic Programming for Air-Drawn Character Recognition Using GPUs

Abstract

Air-drawn character recognition is one of the input methods using human body movements. Time-Space Continuous Dynamic Programming (TSCDP) is one of the algorithms that can implement such a task by detecting pre-defined trajectories from input videos. Since TSCDP requires massive computation, it is hard to make the system work in real-time with a single processor. In this paper, we investigated the frames per second (fps) requirements for the air-drawn character recognition system using TSCDP. We analyzed the dependencies among the calculations of TSCDP for the parallelization using GPUs. We evaluated the computation time with CPU and GPU for desktop and embedded environments. We confirmed that the proposed system works in real-time for real videos in both desktop and embedded environments by comparing with the fps requirements.