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We present a hybrid approach that segments an object by using both color and depth information obtained from views captured from a low-cost RGBD camera and sparsely-located color cameras. Our system begins with generating dense depth information of each target image by using Structure from Motion and Joint Bilateral Upsampling. We formulate the multi-view object segmentation as the Markov Random Field energy optimization on the graph constructed from the superpixels. To ensure inter-view consistency of the segmentation results between color images that have too few color features, our local mapping method generates dense inter-view geometric correspondences by using the dense depth images. Finally, the pixel-based optimization step refines the boundaries of the results obtained from the superpixel-based binary segmentation. We evaluate the validity of our method under various capture conditions such as numbers of views, rotations, and distances between cameras. We compared our method with the state-of-the-art methods that use the standard multi-view datasets. The comparison verified that the proposed method works very efficiently especially in a sparse wide-baseline capture environment. [ABSTRACT FROM AUTHOR]

This paper introduces ScreenX, which is a novel movie viewing platform that enables ordinary movie theatres to become multi-projection movie theatres. This enables the general public to enjoy immersive viewing experiences. The left and right side walls are used to form surrounding screens. This surrounding display environment delivers a strong sense of immersion in general movie viewing. However, naïve display of the content on the side walls results in the appearance of distorted images according to the location of the viewer. In addition, the different dimensions in width, height, and depth among theatres may lead to different viewing experiences. Therefore, for successful deployment of this novel platform, an approach to providing similar movie viewing experiences across target theatres is presented. The proposed image representation model ensures minimum average distortion of the images displayed on the side walls when viewed from different locations. Furthermore, the proposed model assists with determining the appropriate variation of the content according to the diverse viewing environments of different theatres. The theatre suitability estimation method excludes outlier theatres that have extraordinary dimensions. In addition, the content production guidelines indicate appropriate regions to place scene elements for the side wall, depending on their importance. The experiments demonstrate that the proposed method improves the movie viewing experiences in ScreenX theatres. Finally, ScreenX and the proposed techniques are discussed with regard to various aspects and the research issues that are relevant to this movie viewing platform are summarized. [ABSTRACT FROM PUBLISHER]