An Object Detection Algorithm Based on Normalize Gradients
XIONG Lin
ZHANG Xiaofeng
XIA Pengfei
Abstract：In view of the fact that the traditional object detection task is based on sliding window model to extract the features ,which may produce so many redundant windows that will significantly increase the amount of calculation and affect the subsequent feature extraction and classification task .In order to present an extraction algorithm which combines selective search and gradient standardization .First ,selective search algorithm is used to produce a set of the object areas ,which can greatly reduce the search space and produce fewer object areas .Then the object areas are mapped by exploiting the gradient feature normalize .The detection accuracy will be improved by classifying these feature vectors.
Keywords：selective searchnormalize gradientfeature mappingobject detection
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 1909-1911,1916 )