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High efficiency video coding (HEVC) based 3D video coding (3D-HEVC) is the latest 3D video coding standard under development. In 3D-HEVC, most of coding units (CU) select merge modes as their best modes. However, they still have to check a large number of irrelevant candidate modes in mode decision process, which brings significant complexity. In this paper, we propose a low complexity texture mode...
Brain tumor segmentation is one of the main challenging problems in computer vision and its early diagnosis is critical to clinics. Segmentation needs to be accurate, efficient and robust to avoid influences caused by various large and complex biases added to images. This paper proposes a multiple convolutional neural network (CNNs) framework with discrimination mechanism which is effective to achieve...
Recently, a test model for 3D video coding extension of HEVC (3D-HEVC) has been drafted. In the model, a disparity vector (DV) derived from neighbouring blocks (NBDV) is used in the inter-view motion prediction to exploit inter-view redundancy. The accuracy of the derived DV affects prediction efficiency. In the NBDV search process, however, the first available DV among candidate DVs is chosen. It...
This paper analyzes the relationship between macro block (MB) modes and depth values in multiview video plus depth (MVD) format, and proposed a depth based mode decision algorithm for 3D video coding. The depth information was utilized to determine the final mode decision process. The experimental results show the proposed algorithm can reduce the complexity of the mode decision process remarkably...
This paper presents the design and implementation of a real-time 3D video capture and transfer system based on Microsoft Kinect. On the collecting layer, multiple views of texture images and depth images are acquired by 3 Kinect cameras, which are placed as a parallel array. Hole filling and noise filtering techniques are used to fill holes and smooth noise in depth image on the processing layer....
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