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Yufei Zhang 0012

dblp:32/1720-12 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2001
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
2 papers
Computational photography and imaging · 68% Rendering · 25% Visual content generation and editing · 7%
Artificial intelligence
1 paper
3D vision · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational photography and imaging › illumination estimation
illuminant direction estimation
0.122001
Multiple Illuminant Direction Detection with Application to Image Synthesis · IEEE Trans. Pattern Anal. Mach. Intell. 2001
Illuminant Direction Determination for Multiple Light Sources · CVPR 2000
Rendering
image-based rendering
0.012001
Multiple Illuminant Direction Detection with Application to Image Synthesis · IEEE Trans. Pattern Anal. Mach. Intell. 2001
Computer vision › 3D vision
shape from shading
0.012000
Illuminant Direction Determination for Multiple Light Sources · CVPR 2000
Computational photography and imaging
illumination estimation
0.012000
Illuminant Direction Determination for Multiple Light Sources · CVPR 2000
Visual content generation and editing
image generation
0.012001
Multiple Illuminant Direction Detection with Application to Image Synthesis · IEEE Trans. Pattern Anal. Mach. Intell. 2001

Methods — techniques the papers use, named apart from their topics

critical point detection · 0.1least squares estimation · 0.0lambertian shading model · 0.0
YearPublicationVenuePosition
2001 Multiple Illuminant Direction Detection with Application to Image Synthesis
abstract
Pentland observed (1982, 1984) that the human eye is sensitive to the change of intensities. On an image of a smooth surface, the change of intensities is maximal whenever the illuminant direction is perpendicular to the normal of the surface. This motivates us to introduce the concept of critical points, where the surface normal is perpendicular to some light source direction. Apparently, the illuminant direction has a simple geometric relationship with the corresponding critical points. In this paper, for simplicity reasons, we restrict our discussions to the shading of a Lambertian sphere of known size in a multiple distant light source environment. A novel global representation of the intensity function is derived. Based on this intensity characterization, the least-squares and iteration techniques are used to determine critical points and, thus, the light source directions and their intensities if certain conditions are satisfied. The performance of this new approach is evaluated using both synthetic images and real images. As an application, we use it as a tool to determine light sources in real image synthesis. The experimental results show that this technique can be used to superimpose synthetic objects with a real scene.
Yufei Zhang 0012, Yee-Hong Yang
IEEE Trans. Pattern Anal. Mach. Intell.1
2000 Illuminant Direction Determination for Multiple Light Sources
abstract
In this paper, a novel scheme of extracting multiple illuminant directions from an image of a Lambertian sphere of known size is proposed. The illuminant direction detection process is based on the concept of critical points introduced in the paper. We show that the illuminant directions have a close relationship to those critical points and that, by identifying those critical points as many as possible, illuminate direction may be recovered if certain conditions are satisfied. Our preliminary, experimental results show that illumination information can be obtained accurately.
Yufei Zhang 0012, Yee-Hong Yang
CVPR1