Real-time object detection on CUDA

Bourdev, L., Brandt, J.: Robust object detection via soft cascade. In: CVPR (2005)

Charles Brubaker, S., Mullin, M.D., Rehg, J.M.: Towards optimal training of cascaded detectors. In: ECCV06, pp. 325–337 (2006)

Cha, Z., Viola, P.: Multiple-instance pruning for learning efficient cascade detectors. In: NIPS (2007)

Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: CVPR ’05: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), vol. 1, pp. 886–893, Washington, DC, USA, 2005. IEEE Computer Society

Demirkir, C., Sankur, B.: Face detection using look-up table based gentle AdaBoost. In: Audio- and Video-based Biometric Person Authentication 2005, p. 339 (2005)

Freund, Y., Schapire, R.E.: A decision-theoretic generalization of on-line learning and an application to boosting. In: EuroCOLT ’95: Proceedings of the Second European Conference on Computational Learning Theory, pp. 23–37. Springer, London, UK (1995)

Friedman, J., Hastie, T., Tibshirani, R.: Additive logistic regression: a statistical view of boosting. Ann. Stat. 28(2):337–407 (2000)

Herout, A., Jošth, R., Zemčik, P., Hradiš, M.: GP-GPU implementation of the “Local Rank Differences” image feature. In: Proceedings of International Conference on Computer Vision and Graphics 2008, Lecture Notes in Computer Science, pp. 380–390. Springer, Verlag (2008)

Herout, A., Zemčík, P., Hradiš, M., Juránek, R., Havel, J., Jošth, R., Žádník, M.: Pattern recognition, recent advances, chapter low-level image features for real-time object detection, p. 25. IN-TECH Education and Publishing (2009)

Herout, A., Zemčík, P., Juránek, R., Hradiš, M.: Implementation of the “Local Rank Differences” image feature using SIMD instructions of CPU. In: Proceedings of Sixth Indian Conference on Computer Vision, Graphics and Image Processing. IEEE Computer Society (2008)

Hou, C., Ai, H.Z., Lao, S.H.: Multiview pedestrian detection based on vector boosting. In: Proceedings of the 8th Asian Conference on Computer Vision, Part I. Tokyo, Japan, 18–22 November (2007)

Hradiš, M., Herout, A., Zemčík, P.: Local rank patterns—novel features for rapid object detection. In: Proceedings of International Conference on Computer Vision and Graphics 2008, Number 12 in Lecture Notes in Computer Science, pp. 239–248. Springer (2008)

Huang, C., Ai, H.Z., Li, Y., Lao, S.H.: High-performance rotation invariant multiview face detection. PAMI 29(4), 671–686 (2007)

Li, S.Z., Zhu, L., Zhang, Z.Q., Blake, A., Zhang, H.J., Shum, H.: Statistical learning of multi-view face detection. In: ECCV ’02: Proceedings of the 7th European Conference on Computer Vision Part IV, pp. 67–81. Springer, London, UK (2002)

Lienhart, R., Maydt, J.: An extended set of haar-like features for rapid object detection. In: IEEE ICIP 2002, pp. 900–903 (2002)

Schapire, R.E., Singer, Y.: Improved boosting algorithms using confidence-rated predictions. Mach. Learn. 37, 297–336 (1999)

Sochman, J., Matas, J.: Adaboost with totally corrective updates for fast face detection. In: AFGR04, pp. 445–450 (2004)

Šochman, J., Matas, J.: WaldBoost—learning for time constrained sequential detection. In: CVPR ’05: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), vol. 2, 20–26 June (2005)

Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, p. 511 (2001)

Zhang, L., Chu, R., Xiang, S., Liao, S.C., Li, S.Z.: Face detection based on multi-block LBP representation. In: ICB, pp. 11–18 (2007)