Research ArticleOpen accessPhrase in the titleEnhancing Pedestrian Detection Using Context InformationJorge Candido, Mauricio MarengoniDetecting pedestrians among other objects in a digital image is a relevant task in the field of computer vision. This paper presents a method to improve the performance of a pedestrian detection algorithm using context information. A neural network is used to classify the region below pedestrian candidates as being floor or non-floor. We assume that a pedestrian must be … …Journal of Computer Science, Vol. 14, Issue 7 · 6 Aug 2018 · 7,221 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePedestrian Detection in RGB-D Data Using Deep AutoencodersPavel Aleksandrovich Kazantsev, Pavel Vyacheslavovich SkribtsovRecent popularity of RGB-D sensors mostly comes from the fact that RGB-images and depth maps supplement each other in machine vision tasks, such as object detection and recognition. This article addresses a problem of RGB and depth data fusion for pedestrian detection. We propose pedestrian detection algorithm that involves fusion of outputs of 2D- and 3D-detectors based on deep autoencoders. … …American Journal of Applied Sciences, Vol. 12, Issue 11 · 17 Nov 2015 · 6,812 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPedestrian Recognition Based on Multi-Scale Weighted HOGMonther Hussein Al-BsoolPedestrian recognition receives a great attention in recent years due to its importance in traffic accidents identification. Traffic surveillance systems can provide valuable information for pedestrian recognition using computer vision and image processing techniques. Most techniques exploit simple feature extraction and multi-stage feature matching to train classifiers. In this study, Canny edge information and Histogram of Oriented Gradient (HOG) has … …Journal of Computer Science, Vol. 14, Issue 11 · 7 Nov 2018 · 7,158 accessesView PDFCite
Research ArticleOpen accessIn the abstractObject Detection and Classification from Thermal Images Using Region based Convolutional Neural NetworkUsha Mittal, Sonal Srivastava, Priyanka ChawlaIn recent years, object detection and classification has gained so much popularity in different application areas like face detection, self- driving cars, pedestrian detection, security surveillance systems etc. The traditional detection methods like background subtraction, Gaussian Mixture Model (GMM), Support Vector Machine (SVM) have certain drawbacks like overlapping of objects, distortion due to smoke, fog, lightening conditions etc. In this … …Journal of Computer Science, Vol. 15, Issue 7 · 18 Jul 2019 · 9,448 accessesView PDFCite