1. Car Recognition Through SIFT Keypoint Matching
Third Quarter Report
Drew Stebbins, Pd. 6

2. Background:
License plate tracking technology
Need for civilian vehicle recognition
Object detection techniques
SIFT keypoint matching

3. Problem statement: Car recognition fast moving multi-coloured
complex shapes
must identify in real-time

4. Region of Interest Identification:
Hough circle transform
multiple passes

6. SIFT keypoint matching:
Keypoint detection
scale-space extrema detection
keypoint localization
orientation assignment
keypoint descriptor

8. SIFT keypoint matching:
Matching to database images
nearest-neighbour identification based on keypoint description

9. Expectations:
side profile car recognition and categorization
invariant to lighting changes, also small amounts of rotation, translation
multiple cars
moderate detection speed

10. Progress: Region of interest identification
Hough transform circle detector
Scale space extrema detection
Gaussian smoothing function and difference-of-Gaussian

11. Plan for Fourth Quarter:
Finish implementation of SIFT keypoint detection algorithm
Test recognition accuracy on database of testing images taken from TJ student parking lot

12. You just won the game!