Title :
Human Detection Based on Optical Flow and Spare Geometric Flow
Author :
Hong Han ; Minglei Tong
Author_Institution :
Sch. of Electron. Eng., Xidian Univ., Xi´an, China
Abstract :
Different from most of the previous work, we detect motion human by region segmentation and classification through machine learning. In our method, based on optical flow, region segmentation is carried firstly and then, based on geometric flow, Bandelet transform is used to do feature extraction and classification. Some treatments were carried after optical flow field computation to denoising and some improvements in Bandelet transform were used to reduce time cost of feature extraction. The results of motion human detection experiments indicate that the proposed method can segment motion region more clearly and improve the performance of classifier effectively. It can be used to do real-time motion human detection in videos.
Keywords :
feature extraction; geometry; image classification; image denoising; image motion analysis; image segmentation; image sequences; learning (artificial intelligence); object detection; transforms; Bandelet transform; feature extraction; image denoising; machine learning; motion region segmentation; optical flow field computation; real-time motion human detection; region classification; spare geometric flow; videos; Computer vision; Feature extraction; Image motion analysis; Integrated optics; Optical imaging; Optical noise; Transforms; geometric flow; human detection; optical flow; spare representation;
Conference_Titel :
Image and Graphics (ICIG), 2013 Seventh International Conference on
Conference_Location :
Qingdao
DOI :
10.1109/ICIG.2013.96