Monocular Depth Estimation Based on Multi-Scale Depth Map Fusion
نویسندگان
چکیده
منابع مشابه
Multi-view dense depth map estimation
A novel dense depth map estimation algorithm is proposed in order to meet the requirements of N-view plus N-depth representation, which is one of the standardization efforts for the upcoming 3D display technologies. Hence, extraction of multiple depth maps is achieved from multi-view video. Starting from the piecewise planarity assumption of the scene, estimation of 3D structure of the patches,...
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Depth estimation in computer vision and robotics is most commonly done via stereo vision (stereopsis), in which images from two cameras are used to triangulate and estimate distances. However, there are also numerous monocular visual cues— such as texture variations and gradients, defocus, color/haze, etc.—that have heretofore been little exploited in such systems. Some of these cues apply even...
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Estimating an accurate and naturalistic dense depth map from a single monocular photographic image is a difficult problem. Nevertheless, human observers have little difficulty understanding the depth structure implied by photographs. Two-dimensional (2D) images of the real-world environment contain significant statistical information regarding the three-dimensional (3D) structure of the world t...
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Depth cues have been proved very useful in various computer vision and robotic tasks. This paper addresses the problem of monocular depth estimation from a single still image. Inspired by the effectiveness of recent works on multi-scale convolutional neural networks (CNN), we propose a deep model which fuses complementary information derived from multiple CNN side outputs. Different from previo...
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We present a novel method to train machine learning algorithms to estimate scene depths from a single image, by using the information provided by a camera’s aperture as supervision. Prior works use a depth sensor’s outputs or images of the same scene from alternate viewpoints as supervision, while our method instead uses images from the same viewpoint taken with a varying camera aperture. To en...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2021
ISSN: 2169-3536
DOI: 10.1109/access.2021.3076346