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Research Article Open Access
In Computer vision, image segmentation is the process of partitioning a digital image into multiple segments, Human segmentation in photo images is a challenging and important problem. As computer vision researchers have increased attention in segmenting human from a given input image or a video. There are different techniques classified with respect to different approach of segmenting human i.e Exemplar based, part based and some other methods which are using different approaches like shape priors(CRF,MRF), ACF of segmenting human from photo images. In Exemplar approach, exemplar pool is created first and then test images are matched with the exemplars or models. Whereas in part based approach human body can be recovered by assembling set of candidate parts. Both of this approach is having some drawbacks so some other methods are developed for human segmentation. In this paper a straightforward framework to automatically recover human bodies from colour photos is proposed by employing coarse to fine strategy, first detect a coarse torso (CT) using multicue CT detection algorithm and then extract the accurate region of upper body. Then an iterative multiple oblique histogram algorithms is presented o accurately recover the lower body on human kinematics.