Camera/Vision for Geo-Location & Geo-Identification

John S. Zelek

Intelligent Human Machine Interface LabDept. of Systems Design Engineering

University of Waterloo

Why can’t we use GPS everywhere?

Urban canyons

Indoor navigation

1. Introduction - 2/20

What we are trying to do

CameraInertial

Altimeter, Compass+/- GPS =

Accuracy +Location +

Maps +1. Introduction – 3/20

Applications

1. Introduction – 4/20

SLAM

Given:Dead-reck.Ext. sensorWaypoints

Not Known:MapGPS

2. SLAM – 5/20

Trees as landmarks

for triangulati

on

2. SLAM - 6/20

Daniel AsmarSlide 7

Differentiating different trees

2. SLAM – 7/20

2. SLAM – 8/20

Object Category

Recognition

3. Object Detection & Recognition – 9/20

Classes of Objects vs. Instances

2 instances of an individual object(space shuttle)

2 instances of an object face class

2 instances of an

object motorcycle

class3. Object Detection & Recognition – 10/20

Visual vs. Functional classes

There is a wide variation in the

appearance of objects that are categorized

by function. We focus only on

categories related by some

visual consistency only!

3. Object Detection & Recognition – 11/20

Challenges

changes of viewpoint

transformation (translation, rotation, scaling, affine), out-of-plane (foreshortening)

illumination differences

background clutter

occlusion

intra-class variation

3. Object Detection & Recognition – 12/20

Ours

Others

Repeatability of our detector appears to be better!

3. Object Detection & Recognition – 13/20

Object Graphs

3. Object Detection & Recognition – 14/20

3. Object Detection & Recognition – 15/20

3. Object Detection & Recognition – 16/20

4. Structure from Stereo – 17/20

Structure from stereo

Structure from motion4. Structure From Motion – 18/20

5. Context Recognition – 19/20

6. Closing – 20/20

Extra. Features for Recognition & Structure – 21/20

Extra. Features for Recognition & Structure – 22/20