Abstract
In this work, a pedestrian detection system based on still images taken from monocular cameras is proposed. This framework aims to distinctively find each of the sub-objects that defines the main object, and then detects the complete main object by exploiting these sub-objects. In other words, this framework utilizes bottom-to-top approach. Modeling of the objects is realized by using approach of ratio-templates.
Keywords
Computer science
Computer vision
Artificial intelligence
Object detection
Pedestrian detection
Object (grammar)
Pedestrian
Monocular
Template
Pattern recognition (psychology)
Engineering
Subject Areas
Video Surveillance and Tracking Methods
·Computer Vision and Pattern Recognition ·Physical Sciences
Advanced Neural Network Applications
·Computer Vision and Pattern Recognition ·Physical Sciences
Autonomous Vehicle Technology and Safety
·Automotive Engineering ·Physical Sciences
Citations by Year
2012: 1
2018: 1
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Sustainable cities and communities 74%
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