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Ensemble Deep Network for Dense Vehicle Detection in Large Image

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2021, 26(1), pp.45-55
  • DOI : 10.9708/jksci.2021.26.01.045
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : September 17, 2020
  • Accepted : November 30, 2020
  • Published : January 29, 2021

Jae-Hyoung Yu 1 Youngjun Han 1 KIM Jong Kuk 1 Hernsoo Hahn 1

1숭실대학교

Accredited

ABSTRACT

This paper has proposed an algorithm that detecting for dense small vehicle in large image efficiently. It is consisted of two Ensemble Deep-Learning Network algorithms based on Coarse to Fine method. The system can detect vehicle exactly on selected sub image. In the Coarse step, it can make Voting Space using the result of various Deep-Learning Network individually. To select sub-region, it makes Voting Map by to combine each Voting Space. In the Fine step, the sub-region selected in the Coarse step is transferred to final Deep-Learning Network. The sub-region can be defined by using dynamic windows. In this paper, pre-defined mapping table has used to define dynamic windows for perspective road image. Identity judgment of vehicle moving on each sub-region is determined by closest center point of bottom of the detected vehicle's box information. And it is tracked by vehicle's box information on the continuous images. The proposed algorithm has evaluated for performance of detection and cost in real time using day and night images captured by CCTV on the road.

Citation status

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