关键词: 图像序列分析, 变分光流模型, 分数阶微分掩模, 运动目标检测 

Abstract: An adaptive dual fractional order variational optical flow ( ADFOVOF) model was proposed to solve the problem that the current optical flow algorithm cannot segment moving objects in weak texture region under insufficient illumination． The model was an adaption version of dual fractional order optical flow ( DFOVOF) model that adopts fractional differential mask in both，the data term and smoothness term of traditional Horn ＆ Schunck ( HS) model． Specially，the order and size of fractional order differential mask for each region were adjusted by image signal to noise ratio ( SNＲ) whereas，the shape of the fractional order differential mask was regulated by super-pixel that prevents the mask to interfere by surrounding regions． The experiment results show that our algorithm can get accurate optical flow field and obtain clear motion outlines under insufficient illumination or illumination changes scenes． 

Key words: image sequence analysis, variational optical flow model, fraction order differential mask, motion detection