AdaBoost learning for human detection based on histograms of oriented gradients

Chi Chen Raxle Wang, Jenn Jier James Lien

研究成果: Conference contribution

35 引文 斯高帕斯(Scopus)


We developed a novel learning-based human detection system, which can detect people having different sizes and orientations, under a wide variety of backgrounds or even with crowds. To overcome the affects of geometric and rotational variations, the system automatically assigns the dominant orientations of each block-based feature encoding by using the rectangular- and circulartype histograms of orientated gradients (HOG), which are insensitive to various lightings and noises at the outdoor environment. Moreover, this work demonstrated that Gaussian weight and tri-linear interpolation for HOG feature construction can increase detection performance. Particularly, a powerful feature selection algorithm, AdaBoost, is performed to automatically select a small set of discriminative HOG features with orientation information in order to achieve robust detection results. The overall computational time is further reduced significantly without any performance loss by using the cascade-ofrejecter structure, whose hyperplanes and weights of each stage are estimated by using the AdaBoost approach.

主出版物標題Computer Vision - ACCV 2007 - 8th Asian Conference on Computer Vision, Proceedings
版本PART 1
出版狀態Published - 2007
事件8th Asian Conference on Computer Vision, ACCV 2007 - Tokyo, Japan
持續時間: 2007 11月 182007 11月 22


名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
號碼PART 1
4843 LNCS


Other8th Asian Conference on Computer Vision, ACCV 2007

All Science Journal Classification (ASJC) codes

  • 理論電腦科學
  • 電腦科學(全部)


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