Head detection using motion features and multi level pyramid architecture
A two-stage head detection system using motion features is proposed. A multi-level histograms architecture targeting low-resolution images is developed. State of the art motion features including HOOF and MBH have been employed. HOOF has been extended to Relative Motion Distance for better head representation. The results are validated using PETS 2009 dataset and compared to other existing schemes with excellent results.
head detection multi level pyramid architecture histogram of oriented optical flow (hoof) support vector machine (svm) motion boundary histogram