Exploring Visual and Motion Saliency for Automatic Video Object Extraction - 2013 PROJECT TITLE : Exploring Visual and Motion Saliency for Automatic Video Object Extraction - 2013 ABSTRACT: This paper presents a saliency-based video object extraction (VOE) framework. The proposed framework aims to automatically extract foreground objects of interest without any user interaction or the use of any training data (i.e., not limited to any particular type of object). To separate foreground and background regions within and across video frames, the proposed method utilizes visual and motion saliency information extracted from the input video. A conditional random field is applied to effectively combine the saliency induced features, which allows us to deal with unknown pose and scale variations of the foreground object (and its articulated parts). Based on the ability to preserve both spatial continuity and temporal consistency in the proposed VOE framework, experiments on a variety of videos verify that our method is able to produce quantitatively and qualitatively satisfactory VOE results. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution - 2013 Gaussian Blurring-Invariant Comparison of Signals and Images - 2013