Among all the various computer vision applications, automatic logo recognition has drawn great interest from industry as well as various academic institutions. In this paper, we propose an angle-distance map, which we used to develop a robust logo detection algorithm. The proposed angle-distance histogram is invariant against scale and rotation. The proposed method first used shape information and color characteristics to find the candidate regions and then applied the angle-distance histogram. Experiments show that the proposed method detected logos of various sizes and orientations.
KEYWORDS: Visualization, Video, 3D image processing, Stereoscopic displays, Cameras, Visual process modeling, 3D modeling, LCDs, Tablets, 3D visualizations
In this paper, we investigate two error issues in stereo images, which may produce visual fatigue. When two cameras are used to produce 3D video sequences, vertical misalignment can be a problem. Although this problem may not occur in professionally produced 3D programs, it is still a major issue in many low-cost 3D programs. Recently, efforts have been made to produce 3D video programs using smart phones or tablets, which may present the vertical alignment problem. Also, in 2D-3D conversion techniques, the simulated frame may have blur effects, which can also introduce visual fatigue in 3D programs. In this paper, to investigate the relationship between these two errors (vertical misalignment and blurring in one image), we performed a subjective test using simulated 3D video sequences that include stereo video sequences with various vertical misalignments and blurring in a stereo image. We present some analyses along with objective models to predict the degree of visual fatigue from vertical misalignment and blurring.
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