Accelerated Corner-Detector Algorithms

Fast corner-detector algorithms are important for achieving real time in different computer vision applications. In this paper, we present new algo-rithm implementations for corner detection that make use of graphics pro-cessing units (GPU) provided by commodity hardware. The programmable capabilities of modern GPUs allow speeding up counterpart CPU algorithms. In the case of corner-detector algorithms, most steps are easily translated from CPU to GPU. However, there are challenges for mapping the feature selection step to the GPU parallel computational model. This paper presents a template for implementing corner-detector algorithms that run entirely on GPU, resulting in significant speed-ups. The proposed template is used to implement the KLT corner detector and the Harris corner detector, and nu-merical results are presented to demonstrate the algorithms efficiency. 1