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Depth image-based rendering with low resolution depth
2009 16th IEEE International Conference on Image Processing (ICIP), 2009This paper proposes a new approach for depth image-based rendering (DIBR) with low resolution depth using the 3D propagation algorithm. Our novel depth edge enhancement method efficiently corrects and sharpens the depth edges in the propagated depth image using available high resolution color information.
Quang H. Nguyen +2 more
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Intrinsic Depth: Improving Depth Transfer with Intrinsic Images
2015 IEEE International Conference on Computer Vision (ICCV), 2015We formulate the estimation of dense depth maps from video sequences as a problem of intrinsic image estimation. Our approach synergistically integrates the estimation of multiple intrinsic images including depth, albedo, shading, optical flow, and surface contours.
Kong, N., Black, M.
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Imaged Depth Versus True Depth
Proceedings, 2015Summary The use of the term ‘velocity’ to describe both the true propagation velocity and the modelling “velocity” used in processing (what is here termed ‘pro-velocity’) has given rise to a damaging level of confusion whereby a great majority of geoscientists take the depth image to be a good representation of depth in the subsurface. The relationship
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A new depth image quality metric using a pair of color and depth images
Multimedia Tools and Applications, 2016Typical depth quality metrics require the ground truth depth image or stereoscopic color image pair, which are not always available in many practical applications. In this paper, we propose a new depth image quality metric which demands only a single pair of color and depth images.
Thanh-Ha Le +2 more
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Efficient Depth Propagation for Constructing a Layered Depth Image from a Single Image
Computer Graphics Forum, 2014AbstractIn this paper, we propose an interactive technique for constructing a 3D scene via sparse user inputs. We represent a 3D scene in the form of a Layered Depth Image (LDI) which is composed of a foreground layer and a background layer, and each layer has a corresponding texture and depth map.
Satoshi Iizuka +4 more
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Stereoscopic image generation based on depth images
2004 International Conference on Image Processing, 2004. ICIP '04., 2005A depth-image-based rendering system for generating new views is proposed. One important aspect of the proposed system is that the depth maps are pre-processed using an asymmetric filter to smoothen the sharp changes in depth at object boundaries. In addition to ameliorating the effects of blocky artifacts and other distortions contained in the depth ...
Liang Zhang 0014 +2 more
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Depth map generation by image classification
SPIE Proceedings, 2004This paper presents a novel and fully automatic technique to estimate depth information from a single input image. The proposed method is based on a new image classification technique able to classify digital images (also in Bayer pattern format) as indoor, outdoor with geometric elements or outdoor without geometric elements.
Sebastiano Battiato +4 more
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Depth-Aware Image Seam Carving
IEEE Transactions on Cybernetics, 2013Image seam carving algorithm should preserve important and salient objects as much as possible when changing the image size, while not removing the secondary objects in the scene. However, it is still difficult to determine the important and salient objects that avoid the distortion of these objects after resizing the input image.
Jianbing Shen +2 more
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Structural Modeling from Depth Images
IEEE Transactions on Visualization and Computer Graphics, 2015In this work, we present a new automatic system for scene reconstruction of high-level structural models. We start with identifying planar regions in depth images obtained with a SLAM system. Our main contribution is an approach which identifies constraints such as incidence and orthogonality of planar surfaces and uses them in an incremental ...
Thanh Nguyen 0002 +2 more
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2019
As robots are developed for large-scale applications in autonomous driving, package delivery, and agriculture, there is a growing need for affordable and reliable depth sensing. Robots use active illumination sensors like scanning LIDAR and depth cameras to perceive their worlds. Scanning LIDAR is prevalent because it offers long-range, robust sensing,
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As robots are developed for large-scale applications in autonomous driving, package delivery, and agriculture, there is a growing need for affordable and reliable depth sensing. Robots use active illumination sensors like scanning LIDAR and depth cameras to perceive their worlds. Scanning LIDAR is prevalent because it offers long-range, robust sensing,
openaire +1 more source