<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chen, Jie;  *Duan, Ling-Yu;  Gao, Feng;  Cai, Jianfei;  Kot, Alex C.;  Huang, Tiejun</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A low complexity interest point detector</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Signal Processing Letters</style></secondary-title><short-title><style face="normal" font="default" size="100%">A low complexity interest point detector</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Interest Point Detectors; Laplacian of Gaussian; Scale-space; Scale-space representation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014/2</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.engineeringvillage2.org/search/results/fulltext.url?docID=cpx_M74829d86148f5ff1a0dM7e8410178163125</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">22</style></volume><pages><style face="normal" font="default" size="100%">172-176</style></pages><isbn><style face="normal" font="default" size="100%">1070-9908</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom7><style face="normal" font="default" size="100%">000342159700004</style></custom7><section><style face="normal" font="default" size="100%">172</style></section></record></records></xml>