Results 261 to 270 of about 540,279 (314)

Depth-Aware Image Seam Carving

IEEE Transactions on Cybernetics, 2013
Image 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, Xuelong Li
exaly   +4 more sources

Image Composition with Depth Registration

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
Handling occlusions is still a challenging problem for image composition. It always requires the source contents to be completely in front of the target contents or needs manual interventions to adjust occlusions, which is very tedious. Though several methods have suggested exploiting priors or learning techniques for promoting occlusion determination,
Zan Li, Wencheng Wang, Fei Hou
openaire   +1 more source

Diffraction Imaging in Depth

69th EAGE Conference and Exhibition incorporating SPE EUROPEC 2007, 2007
ABSTRACTHigh resolution imaging is of great value to an interpreter, for instance to enable identification of small scale faults, and to locate formation pinch‐out positions. Standard approaches to obtain high‐resolution information, such as coherency analysis and structure‐oriented filters, derive attributes from stacked, migrated images.
T.J. Moser, C.B. Howard
openaire   +1 more source

Compression of the layered depth image

Proceedings DCC 2001. Data Compression Conference, 2002
A layered depth image (LDI) is a new popular representation and rendering method for objects with complex geometries. Similar to a two-dimensional (2-D) image, the LDI consists of an array of pixels. However, unlike the 2-D image, an LDI pixel has depth information, and there are multiple layers at a pixel location.
Jiangang Duan, Jin Li
openaire   +2 more sources

Depth aware image dehazing

The Visual Computer, 2021
Image dehazing aims to remove the haze noise and restore the image content from hazy images. It is a challenging task because of the unbalanced distribution of the haze noise and the variety of the image contents. Most existing methods apply convolutional neural networks to learn the dehazing process by blind end-to-end training, which relies on the ...
Fei Yang, Qian Zhang
openaire   +1 more source

Image Outpainting with Depth Assistance

2021
In some scenarios such as autonomous diriving, we can get a sparse point cloud with a large field of view, but an RGB image with a limited FoV. This paper studies the problem of image expansion using depth information converted from sparse point cloud projection. General image expansion tasks only use images as input for expansion.
Lei Zhang 0116   +4 more
openaire   +1 more source

Depth annotations: Designing depth of a single image for depth-based effects

Computers & Graphics, 2018
We present a novel pipeline to generate a depth map from a single image that can be used as input for a variety of artistic depth-based effects. In such a context, the depth maps do not have to be perfect but are rather designed with respect to a desired result.
Liao, J. (author)   +2 more
openaire   +3 more sources

Probing depth in monocular images

Biological Cybernetics, 1987
It is generally expected that depth (distance) is the internal representational primitive that corresponds to much of the perception of 3D. We tested this assumption in monocular surface stimuli that are devoid of distance information (due to orthographic projection and the chosen surface shape, with perspective projection used as a control) and yet ...
K A, Stevens, A, Brookes
openaire   +2 more sources

Motion, depth, and image flow

Proceedings., IEEE International Conference on Robotics and Automation, 2002
Motion relative to a surface is addressed. Image flow can be caused either by motion of objects in the world or by motion of the eye through the world. If knowledge exists of eye motion, dense range maps can be computed locally for all stationary object pixels.
James S. Albus, Tsai Hong
openaire   +1 more source

Home - About - Disclaimer - Privacy