A Real-time Video Processing Implementation with Massively Parallel Computation Support

Recently, performance of mobile device's processor has advanced dramatically. There are many researches to utilize the processor computing ability to maximize application performance. In the field of augmented reality (AR), video stream processing is an application that requires large amount of computing powers, from the real-time processing point of view. However, due to nature of mobile platforms, unnecessary overheads should be minimized to acquire higher performance. In this paper, we introduce OpenCL based video frame segmentation to minimize unnecessary overhead in video processing applications, with dynamically changing the local work group size. Our prototype system show at most 2.3 times speed-up compared to well-known, de-facto image processing library OpenCV.