yoloYou only look once v3 (YOLOv3)YouTubeYOLOv5YOLOv8YOLO-RYOLOYolov5YOLOv7-tinyYOLOXYou only look once (YOLO)
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Z numberZERNIKEZEISSZero Parallax SettingZoom FatigueZ-type SchlierenZero-Shot ClassificationZebra EmbryoZernike polynomialZERNIKE MOMENTS
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0.8um pixel
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180 degree images1-bit matrix completion100 Hue test108 Megapixel1/f noise1st and 2nd FM generation 3D halftoning133-MEGAPIXEL1 MICRON PIXELS
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2D AND 3D CONVERTIBLE DISPLAY2.5D printing2D/3D imaging, high performance computing, imaging systems, efficient computations and storage2.5D PRINTING2.5 D printing2D printing2-D barcodes2D-TO-3D CONVERSION ARTIFACTS2AFC2D2.5D2D VIEWS2D DCT2.5D reconstruction2D-plus-depth video2D and 3D video2D metrics2-d scale2D to Hologram conversion
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3D Compression3D Computer Graphics3D object shape3D Models3d localization3-D RECONSTRUCTION3D MODELLING3D Image Processing3D RANGE IMAGING3D Video Conferencing3D Quality3D shape analysis360-deg quality assessment360-DEGREE IMAGE3D SHAPE INDEXING AND RETRIEVAL3D SCENE RECONSTRUCTION AND MODELING3D and 2D3D print3D halftoning3D-human body detection3D recursive search3D Video3-T pixel3D Meshes3D SALIENCY3D reconstruction3DMM3D Compression and Encryption3D VISUALIZATION3D-CNN3D Scene Reconstruction3D Lidar3D Iterative Halftoning360° STEREO PANORAMAS3D MESH3D displays3D communications360-degree video3DViewers3DSR3D Gaussian splatting360-degree3D Display3D MESHES3D surface structure based halftoning3D COMPRESSION AND ENCRYPTION3D glasses3D vision3D3D encoding3D IMAGE3d video3D STIMULI3D-printing3d3D Range Data Encoding360-degree imaging3D Color Printing3D Reconstruction360-Degree Video Technology3D PROFILE3D cinema and TV3D TV3D USER INTERFACES3D DISPLAY3D-high efficiency video coding3D visual representation360 Video3A ALGORITHMS3-D SHAPE RECOVERY360x3D scene capture3d mapping3D RECOVERY3D printer3D INTERACTION360° VIDEO3D imaging3D audio3D ACQUISITION ARCHITECTURE3D range geometry3D digitization and dissemination3D localization and mapping3D Print Appearance3D colour Digital Image Correlation3D-assisted features3D localization3D/4D SCANNING3D projector35MM FILM DIGITIZATION3D mesh simplification3D human-centered technologies3D point cloud3D Scene Reconstruction and Modeling3D-Anisotropic smoothing3DCNN3D depth sensing3D range scanning360° video3ARRI footage3D Curvelet360 IMAGING3D HALFTONING3D Immersion3D Vision3D digital halftoning3D RECONSTRUCTION3D rigid transformations3D modeling3D/2D Visuals3D Point Cloud3D affine transformation3D recovery3D Printing3D capture3D scanning3D Mapping3D modelling360 degree images3D Range Data Compression3D shape3D PRINTER3D Communications360-degree content3D printing3D-HEVC3D adaptive halftoning3D Data Sources3D Halftoning3D camera3D Digital Image Correlation3D image compression3D Tracking3D EDUCATIONAL MATERIAL3D Video Communications3D/4D DATA PROCESSING AND FILTERING3D Shape Indexing and Retrieval3D scene flow estimation3D connected tube model360-degree videos3D Modeling3D STACK3D surface reproduction3D Range Data360-degree Image3D model3D Imaging3D compression3D TRANSFORMATION3D warping3D objects3D scene classification3D video processing3D optical scans3D data processing3D surface3D Saliency3D depth-map360-degree video streaming360-video360VR3D/4D Data Processing and Filtering3D mapping and localization3D stereo vision3D perception360 panorama360 degrees video360-degree art exhibition3D CAMERAS360-degree image projection3D-LUT3D video3D/4D Scanning3D MODEL3D PRINTING3D face alignment360-degree images3D Object Detection3D Morphable Model3D Telepresence3D Data Processing3D DIGITIZATION METHOD FOR OIL PAINTINGS3D-shooting3D position measurement of people3D theater program listing3D Measurement3D refinement3D display3D-color perception3D mesh3D shape indexing and retrieval
In this paper we focus on using single frame videos from a moving camera with pure horizontal translation. We make use of the fact that "3D shape reconstruction in Euclidean space is not necessarily required, but information of dense matching points is basically enough to synthesize
new viewpoint images". The scene geometry and camera motion can be inferred by factorization of feature coordinates over a series of frames. We consider zero convergence angle and unit translation for parameterization of Fundamental Matrix for pure translation as the basis for predicting the
pairs. We generated a cost function that selects the best matching stereo from the given set of frames using Fundamental Matrix Estimation (FME). The predicted scenes are compared with existing methods on the basis of their Peak Signal to Noise Ratio and graphically displayed. The generated
frames are also compared using a disparity map and the results are explained in the paper.
This document provides an overview of the 2017 Stereoscopic Displays and Applications conference (the 28th in the series) and an introduction to the conference proceedings.