Open Access
Int. J. Simul. Multidisci. Des. Optim.
Volume 10, 2019
Article Number A15
Number of page(s) 9
Published online 23 September 2019
  1. N. Dalal, B. Triggs, Histograms of Oriented Gradients for Human Detection, in: Conference on Computer Vision and Pattern Recognition , 2005 [Google Scholar]
  2. P. Dollàr, Z. Tu, P. Perona, S. Belongie, Integral channel features, in: Proceedings of the British Machine Vision Conference , 2009, pp. 91.1–91.11 [Google Scholar]
  3. P. Dollaár, R. Appel, S. Belongie, P. Perona, Fast feature pyramids for object detection, in: Transactions on pattern analysis and machine intelligence (TPAMI) , 2014 [Google Scholar]
  4. S. Ren, K. He, R. Girshick, J. Sun, Faster R-CNN: towards real-time object detection with region proposal networks, in: Advances in Neural Information Processing Systems 28 (NIPS) , 2015 [Google Scholar]
  5. J. Redmon, S. Divvala, R. Girshick, A. Farhadi, You only look once: unified, real-time object detection, Computer Vision and Pattern Recognition , 2016 [Google Scholar]
  6. L. Zhang, B. Wu, R. Nevatia, I. Systems, L. Angeles, Pedestrian Detection in Infrared Images based on Local Shape Features, in: Computer Vision and Pattern Recognition (CVPR) , 2007 [Google Scholar]
  7. D. Olmeda, J.M. Armingol, Contrast Invariant Features for Human Detection in Far Infrared Images, in: Intelligent Vehicles Symposium (IV) , 2012 [Google Scholar]
  8. D. Olmeda, Pedestrian detection in far infrared images, Ph.D. dissertation, 2013 [Google Scholar]
  9. R. Brehar, C. Vancea, S. Nedevschi, Pedestrian detection in infrared images using aggregated channel features, in: Intelligent Computer Communication and Processing (ICCP) , 2014 [Google Scholar]
  10. A. Blum, T. Mitchell, Combining labeled and unlabeled data with co-training, in: COmputational Learning Theory (COLT) , 1998 [Google Scholar]
  11. A. Levin, P. Viola, O.M. Way, Y. Freund, Unsupervised improvement of visual detectors using co-training, in: International Conference on Computer Vision (ICCV) , 2003 [Google Scholar]
  12. P.M. Roth, C. Leistner, A. Berger, H. Bischof, Multiple instance learning from multiple cameras, in: Conference on Computer Vision and Pattern Recognition Workshop (CVPRW) , 2010 [Google Scholar]
  13. S.J. Krotosky, M.M. Trivedi, Mutual information based registration of multimodal stereo videos for person tracking, in: Computer Vision and Image Understanding (CVIU), 2007 [Google Scholar]
  14. J.-Y. Bouguet, Jean-yves bouguet's matlab toolbox for calibrating cameras, 2015, [Google Scholar]
  15. Z. Shi, T. Wei, M.K. Taghi, Boosted Noise Filters for Identifying Mislabeled Data, Department of Computer Science and Engineering Florida Atlantic University, 2005 [Google Scholar]
  16. C.L. Zitnick, P. Dollàr, Edge boxes: locating object proposals from edges, in: European Conference on Computer Vision (ECCV) , 2013 [Google Scholar]

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