Building Recognition

1
Building Recognition

• Landry Huet
• Sung Hee Park
• DW Wheeler

2
Problem Statement

• Identify Stanford buildings from photos
• 16 buildings
• Database of 300 pictures
• Fast enough to implement real time system

3
Project Outline
1. Color histogram matching 2. SIFT feature
matching 3. Image-by-image comparison
4
Approach and Results

• Timing speed-up
• Find buildings in database that have similar
  color properties
• Use kd-tree to find images with the most SIFT
  feature matches
• Time reduced from 34 seconds to 22 seconds

5
Approach and Results

• Accuracy improvement
• Distinguish buildings by both color information
  and SIFT features
• Use HSV color representation and color
  normalization to be invariant to light conditions
• Measure average error between inlier features
  using ransac algorithm

6
Work Distribution

• Landry Huet
• Feature space search, kd-tree structure,
  photography
• Sung Hee Park
• Database interface, SIFT matching, Ransac,
  vanishing points, photography
• DW Wheeler
• Color histograms, photography