A new method is proposed in this paper for feature extraction based on geometric flow of images and the second generation of Bandelet transformation

where Bandelet coefficients and their statistical values were extracted as the feature of human images.Afterwards the full body and body parts classifier were trained on AdaBoost algorithm.At last

likelihoods of each body parts were computed combined with Bayesian decision-based approach to perform human detection.The results of human detection experiments indicate our proposed feature extraction method's better capability in describing human characteristics while effectively improving the performance of classifier.Combined with body parts detection

our proposed human detection method well enhanced the robustness of human detection task in both static and moving images.