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Moving vehicle detection using oriented histograms of differential flow and extreme learning machine

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author:

Kang, L. (Kang, L..) [1] | Yu, Y. (Yu, Y..) [2]

Indexed by:

Scopus

Abstract:

Detecting vehicle in video is a challenging problem owing to the motion of vehicle, camera and background, and to variations of speed. This paper proposes a classifier-based supervised method to detect moving vehicle from a moving camera. Motion descriptors based on oriented histograms of differential optical flow be able to describe the motion pattern of the object from changing background. And Extreme Learning Machine provides excellent generalization performance at fast speed. Our sample images taken by a camera in helicopter include 2000 images. Experiment results shown that this proposed method has not only overall discrimination performance but also low computational cost. © Springer-Verlag Berlin Heidelberg 2015.

Keyword:

Differential optical flow; Extreme learning machine; Histogram of oriented gradient; Optical flow

Community:

  • [ 1 ] [Kang, L.]College of Mathematics and Computer Science, Fuzhou University, 2 Xue Yuan Road, University Town, Fuzhou, China
  • [ 2 ] [Yu, Y.]College of Mathematics and Computer Science, Fuzhou University, 2 Xue Yuan Road, University Town, Fuzhou, China

Reprint 's Address:

  • [Kang, L.]College of Mathematics and Computer Science, Fuzhou University, 2 Xue Yuan Road, University Town, China

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Source :

Lecture Notes in Electrical Engineering

ISSN: 1876-1100

Year: 2015

Volume: 336

Page: 371-378

Language: English

Cited Count:

WoS CC Cited Count:

30 Days PV: 1

Affiliated Colleges:

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管理员  2020-11-20 10:51:58  创建

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