Vision Algorithms and embedded solution for pedestrian detection with far infrared camera

被引：0

作者：

Muresan, Mircea Paul ^{[1
]}

Brehar, Raluca ^{[1
]}

Nedevschi, Sergiu ^{[1
]}

机构：

[1] Tech Univ Cluj Napoca, Dept Comp Sci, Cluj Napoca, Romania

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTER COMMUNICATION AND PROCESSING (ICCP) | 2014年

关键词：

Pedestrian detection; Infrared Imagery; Driver Assistance; Artificial Neural Networks; ensemble algorithms; genetic algorithms; Histogram of oriented Gradients; embedded programming;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

in the automotive industry the issue of safety remains a major priority. This aspect is not focused just on the driver but also on the other participants of the traffic like the pedestrians. This paper describes a pedestrian detection system where three different classification methods are used for detecting pedestrians with a far infrared camera. The three methods are tested and compared on variable number of features in order to obtain a scalable solution. The authors propose a low cost embedded implementation for the classification method that has proven to be best with respect to the accuracy and training time, taking the HOG as features descriptors for the region of interest

引用

页码：133 / 136

页数：4

共 10 条

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