A low complexity interest point detector - Chen, Jie; *Duan, Ling-Yu; Gao, Feng; Cai, Jianfei; Kot, Alex C.; Huang, Tiejun (IEEE Signal Processing Letters, 2014)
Interest point detection is a fundamental approach to feature extraction in computer vision tasks. To handle the scale invariance, interest points usually work on the scale-space representation of an image. In this letter, we propose a novel block-wise scale-space representation to significantly reduce the computational complexity of an interest point detector. Laplacian of Gaussian (LoG) filtering is applied to implement the block-wise scale-space representation. Extensive comparison experiments have shown the block-wise scale-space representation enables the efficient and effective implementation of an interest point detector in terms of memory and time complexity reduction, as well as promising performance in visual search.
Keywords: Interest Point Detectors; Laplacian of Gaussian; Scale-space; Scale-space representation