Fast Vehicle Detection with Lateral Convolutional Neural Network

Chen Hang He, Kin Man Lam

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

In this paper, we propose a fast vehicle detector for traffic surveillance. We first explore using different feature layers from a deep residual network to perform vehicle detection. Experiment results show that the high-resolution features from earlier feature layers contain more structural information, which is good to achieve fine-grained localization but yields low recall rates. The low-resolution features in the deep layers contain semantically strong information, which is good to represent the objectness but too coarse to achieve accurate localization. Therefore, we decouple the localization and objectness prediction from a single layer. Instead, we employ a lateral network that takes the features from earlier layers as input and outputs the localization residual. Our proposed detector can achieve fast detection at a rate of 28 frames/s, and a mean average precision (mAP) of 67.25% in the DETRAC vehicle detection benchmark.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2341-2345
Number of pages5
ISBN (Print)9781538646588
DOIs
Publication statusPublished - 15 Apr 2018
Event2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
Duration: 15 Apr 201820 Apr 2018

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2018-April
ISSN (Print)1520-6149

Conference

Conference2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
CountryCanada
CityCalgary
Period15/04/1820/04/18

Keywords

  • Convolutional neural network
  • Vehicle detection

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Cite this