Volume 8 Number 4 (Apr. 2013)
Home > Archive > 2013 > Volume 8 Number 4 (Apr. 2013) >
JCP 2013 Vol.8(4): 1050-1057 ISSN: 1796-203X
doi: 10.4304/jcp.8.4.1050-1057

Target Detection and Pedestrian Recognition in Infrared Images

Jiabao Wang, Yafei Zhang, Jianjiang Lu, and Yang Li
Institute of Command Automation, PLA Univ. of Sci. and Tech., Nanjing, 210007, China

Abstract—By improving the local contrast between targets and background in the static infrared images, a simple and effective background model is proposed to detect targets. At the same time, a novel learning algorithm is presented for training a discriminatively trained, part-based model with only positives images, for pedestrian recognition. The background models are constructed based on the static infrared images by morphological operations. Meanwhile, the learning algorithm is based on the ramp loss function, which can filter out the false negatives from the collected negative examples. It has a great advantage on training the deformable part models with latent variables when the dataset has a large number of noisy examples. Experiments manifest that our background model can achieve a high precision in target detection and the discriminative part model trained by the proposed learning approach can recognize the targets well and truly, with the help of target detection.

Index Terms—infrared images, target detection, pedestrian recognition, ramp loss, stochastic gradient descent

[PDF]

Cite: Jiabao Wang, Yafei Zhang, Jianjiang Lu, and Yang Li, " Target Detection and Pedestrian Recognition in Infrared Images," Journal of Computers vol. 8, no. 4, pp. 1050-1057, 2013.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
  • Nov 14, 2019 News!

    Vol 14, No 11 has been published with online version   [Click]

  • Dec 16, 2019 News!

    Vol 14, No 12 has been published with online version   [Click]

  • Sep 16, 2019 News!

    Vol 14, No 9 has been published with online version   [Click]

  • Aug 16, 2019 News!

    Vol 14, No 8 has been published with online version   [Click]

  • Jul 19, 2019 News!

    Vol 14, No 7 has been published with online version   [Click]

  • Read more>>