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author:

Cai, Y. (Cai, Y..) [1] | Li, L. (Li, L..) [2] | Ni, S. (Ni, S..) [3] | Lv, J. (Lv, J..) [4] | Zeng, W. (Zeng, W..) [5] | Yuanlong, Y. (Yuanlong, Y..) [6]

Indexed by:

Scopus

Abstract:

Detecting vehicles in video is a challenging problem owing to the motion of vehicles, the camera and the background and to variations of speed. This paper proposes a classifier based supervised method to detect moving vehicles from a moving camera. Dense scale invariant feature transform (dense SIFT) descriptors are used as features to describe the pattern of the object. 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 good overall performance but also low computational cost. © 2015 IEEE.

Keyword:

dense scale invariant feature transform; extreme learning machine; low computational cost; Moving vehicle detection

Community:

  • [ 1 ] [Cai, Y.]Fujian Provincial Power Co. Ltd., State GRIP, China
  • [ 2 ] [Li, L.]Fujian Provincial Power Co. Ltd., State GRIP, China
  • [ 3 ] [Ni, S.]Fujian Yirong Information Technology Co. Ltd., State GRIP, China
  • [ 4 ] [Lv, J.]Fujian Yirong Information Technology Co. Ltd., State GRIP, China
  • [ 5 ] [Zeng, W.]Fujian Yirong Information Technology Co. Ltd., State GRIP, China
  • [ 6 ] [Yuanlong, Y.]College of Mathematics and Computer Science, Fuzhou University, Fuzhou, Fujian, China

Reprint 's Address:

  • [Yuanlong, Y.]College of Mathematics and Computer Science, Fuzhou UniversityChina

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Source :

2015 IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO 2015

Year: 2015

Page: 1614-1618

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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