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The wide availability of stereoscopic 3D displays created a considerable market for content producers. This encouraged researchers to focus on methods to alter and process the content for various purposes. This study concentrates on user assisted image segmentation and proposes a method to extend previous techniques on monoscopic image segmentation to stereoscopic footage with minimum effort. User assistance is required to indicate the representative locations of an image as object and background regions. An MRF based energy minimization technique is utilized where user inputs are applied only on one of the stereoscopic pairs. A key contribution of the proposed study is the elimination of dense disparity estimation by introducing a sparse feature matching idea. Segmentation results are evaluated by objective metrics on a ground truth stereo segmentation dataset and it can be concluded that competitive results with minimum user interaction have been obtained even without dense disparity estimation.