Geometric Feature Pruning

Geometric Feature Pruning uses the semantic tags on maps to form a feature based on geometric relationship of tags to reduce search space of image localization problem.

Semantic tags:
Google map API allows us to extract semantic tag such as
road
man-made building...etc
Google Style Map Spec

Geometric Feature:
In Madrid example, the angle between road is used.

Experimental Setup:
The Madrid example is used to verify the idea.

The full search space is a rectangle around the ground truth location.

The search space is 425 m in width and height which is about 0.03 of size (m^2/m^2) of city.

Semantic map:

(a) road

(b) building and space

We have 9 maps with the same size of example image to cover the search space.

Geometric feature:

We develop an intersection descriptor which can be automatically extracted from styled Google Map.

Two features in intersection descriptor can be used for pruning search space.

1. the number of corners at the intersection.

2. the angle of the corner.

Experiment:

Query Intersection is computed from rectified images.

Here "Number of Corner: 2" and "Angle: 73.88" are used to prune the search space.

The ground truth location is at the center of image.

The degree of matching score can be represented by radius of blue circle.

The radius r is computed by

r = R * exp(-d(ang0,ang1)/sigma)

where R, sigma is a constant. d(. , .) is 2 norm distance of query angle and angle in database.

Another Example: Paris

The Paris Example

Query: "Number of Corner: 4" and "Angle: 57.68" are used to prune the search space.

Result:

The ground truth location is at the center of image.