Low Complexity Corner Detector Using CUDA for Multimedia Applications
17 April 2011
High speed feature detection is a requirement for many realtime multimedia and computer vision applications. In previous work, the Harris and KLT algorithms were redesigned to increase the performance by reducing the algorithmic complexity, resulting in the Low Complexity Corner Detector algorithm. To attain further speedup, this paper proposes the implementation of this low complexity corner detector algorithm on a parallel computing architecture, namely a GPU using Compute Unified Device Architecture (CUDA). We show that the low complexity corner detector is 2-3 times faster than the Harris corner detector algorithm on the same GPU platform.
