Object Detection and Classification Using GPU Acceleration

被引：2

作者：

Prabhu, Shreyank ^{[1
]}

Khopkar, Vishal ^{[1
]}

Nivendkar, Swapnil ^{[1
]}

Satpute, Omkar ^{[1
]}

Jyotinagar, Varshapriya ^{[1
]}

机构：

[1] Veermata Jijabai Technol Inst, Mumbai 400019, Maharashtra, India

来源：

COMPUTATIONAL VISION AND BIO-INSPIRED COMPUTING | 2020年 / 1108卷

关键词：

Graphics processer unit; GPU; Object detection; Image processing; HOG; OpenCL; Self-driving cars; SVM;

D O I：

10.1007/978-3-030-37218-7_18

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In order to speed up the image processing for self-driving cars, we propose a solution for fast vehicle classification using GPU computation. Our solution uses Histogram of Oriented Gradients (HOG) for feature extraction and Support Vector Machines (SVM) for classification. Our algorithm achieves a higher processing rate in frames per second (FPS) by using multi-core GPUs without compromising on its accuracy. The implementation of our GPU programming is in OpenCL, which is a platform independent library. We used a dataset of images of cars and other non-car objects on road to feed it to the classifier.

引用

页码：161 / 170

页数：10

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