A survey of Light Source Detection Methods Nathan Funk University of Alberta Nov. 2003.

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Presentation transcript:

A survey of Light Source Detection Methods Nathan Funk University of Alberta Nov. 2003

What is Light Source Detection? Problem of Computer Vision Typically given a single image of a scene Where is the light coming from? Goal: Recover directions, intensities, and types (directional, point, area…) of light sources.

Example 1

Example 2

Motivations, Applications Scene reconstruction Find shape of objects Shape from shading Augmented reality Place an artificial object in a real scene Wrong lighting is obvious to us [Zhang “Illumination Determination…”, 2000] Artificial Real

Common Assumptions Directional light sources Lambertian surface Smooth surfaces Other: Analysis of specific object Known number of sources Orthographic projection

Pentland (1982) Statistical approach Analyse intensity changes in X and Y directions Only single source Similar methods: Lee & Rosenfeld (1985) – targeted for sphere Brooks & Horn (1985) – attempt to recover shape X Y

Weinshall (1990) Analyse intensities along occluding boundaries Look for extreme points of intensity profile Single source Yang & Yuille (1991) use similar approach Extended to detect multiple sources [Nillius “Automatic Estimation…”, 2001]

Hougen & Ahuja (1993) Arbitrary known geometry Known number of sources Solve set of irradiance equations (one for each sampled point in the image) Add illustration

Zhang & Yang (2000) Uses sphere model Find cut-off curves  High precision estimation of direction Each cut-off curves identifies the direction of a light source Detects multiple sources

Wang & Samaras (2002) Similar to Zhang & Yang Known geometry Map arbitrary surface to sphere Then apply same techniques as Zhang

Li, Lin, Lu, and Shum (2003) “Multiple-cue Illumination Estimation” Uses shading, shadows, and specular reflections First technique to deal with textured objects

Feature Comparison Arbitrary Given Geometry Unknown Geometry Multiple Sources High Precision Textured Surfaces Pentland Weinshall Yang & Yuille Hougen & Ahuja Zhang & Yang Wang & Samaras Li, Lin, Lu & Shum

Challenges Processing real images is difficult! Arbitrary unknown objects Textured objects Other types of light sources (not just directional ones) Reflected light