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Document details - A histogram-refinement Histogram-of-Oriented-Gradient Object and Pedestrian Detector

Journal Volume 9, Issue 6, November - December 2020, Article 9752202 Daniel Asher Mitchell, Harvey Barnett Mitchell , " A histogram-refinement Histogram-of-Oriented-Gradient Object and Pedestrian Detector" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 9, Issue 6, November - December 2020 , pp. 027-031 , ISSN 2278 - 6856.

A histogram-refinement Histogram-of-Oriented-Gradient Object and Pedestrian Detector

    Daniel Asher Mitchell, Harvey Barnett Mitchell

Abstract

Abstract:The Histogram-of-Oriented-Gradient (HOG) is widelyused forobject and pedestrian detection. The basic idea of HOG is that theappearance of an object can be characterized by the spatial distribution of the intensity of the local gradients and their directions. In this article we describe a new HOG detectorin which we use the method of histogram refinement to split the traditional HOG vector into two complementary vectors which we subsequently fuse together. The new HOG has an enhanced performance but at the same time is fully compatible with the traditional HOG. Experimental results on the INRIA pedestrian detection database shows that for noisy input images the histogram-refined HOG significantly outperforms the traditional HOG detector.

  • ISSN: 22786856
  • Source Type: Journal
  • Original language: English

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