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

Artificial

[Zhang “Illumination Determination…”, 2000]

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 Y  X Similar methods:   Lee & Rosenfeld (1985) – targeted for sphere Brooks & Horn (1985) – attempt to recover shape

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]

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

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

Challenges

 Processing real images is difficult!

 Arbitrary unknown objects  Textured objects  Other types of light sources (not just directional ones)  Reflected light