8/14/2019 Traffic Light Triggering For Motorbikes Using Computer Vision Presentation

1/8

1

Vision Based Traffic Light Triggering for Motorbikes

Tommy Chhengtcchheng*at*ucsd.edu

CSE 190: Projects In Computer VisionInstructor: Prof. Serge Belongie

15 March 07

8/14/2019 Traffic Light Triggering For Motorbikes Using Computer Vision Presentation

2/8

2

Vision Based Traffic Light Triggering for Motorbikes

Goal: To create a computer vision algorithm to detect

incoming motorbike traffic for traffic light triggering.

Motivation: Current traffic light triggers do not work on motorbikes

General Idea: From video footage, track motion of objects and

determine if the object's trajectory is intended incoming

traffic.

8/14/2019 Traffic Light Triggering For Motorbikes Using Computer Vision Presentation

3/8

3

Vision Based Traffic Light Triggering for Motorbikes

Motion Segmentation Background subtraction Defining the background image for subtraction:

A still image from a set time- Not robust- Slight movement to the camera will produce noise.- Difficult to automate updates.

Previous Frame- Difficult to pick up differences of slow moving objects.

Sliding Temporal Average- Compute average frame from the previous n frames.

8/14/2019 Traffic Light Triggering For Motorbikes Using Computer Vision Presentation

4/84

Vision Based Traffic Light Triggering for Motorbikes

Connected Component Labeling

Label the foreground blobs for tracking.

Accomplished by computing the distance fromprevious objects and attaching it to nearest one withina threshold. If not, create a new label.

8/14/2019 Traffic Light Triggering For Motorbikes Using Computer Vision Presentation

5/8

5

Vision Based Traffic Light Triggering for Motorbikes

Lighting Conditions for Motion Segmentation

Adversely affect motion segmentation

Use dual colorspace selection During night time, RGB gives optimal results due to the

headlights of the motorbikes and low noise. During day time, opponent color blue/yellow channel.

Reduce effects of luminance. L*A*B* too nonlinear for lowresolution images.

Original RGB Subtract Opponent color B/Y Subtract

8/14/2019 Traffic Light Triggering For Motorbikes Using Computer Vision Presentation

6/8

6

Vision Based Traffic Light Triggering for Motorbikes

Tracking

Connected Component Labeling process labeledobjects in each frame.

Can save position information regarding each object.

Objects labeled in frame

Trajectories of objects in frame

8/14/2019 Traffic Light Triggering For Motorbikes Using Computer Vision Presentation

7/8

7

Vision Based Traffic Light Triggering for Motorbikes

Tracking Problems

With simplified tracking determination, cross trafficcan easily steal the intended tracking(or vice versa).

Even if the tracking does not entirely work, partialtracking maybe enough to do the job.

Use RANSAC to determine the partial trajectories.

Traffic mis-tracked RANSAC to get partial trajectories

8/14/2019 Traffic Light Triggering For Motorbikes Using Computer Vision Presentation

8/8

8

Vision Based Traffic Light Triggering for Motorbikes

Steps I did not have time for: Actual classification system

Now the traffic detection problem is reduced to a linefitting/classification problem.

Ideas include feeding in annotated correct trajectories andtesting by a difference on the test data.

Extensive training/testing set Difficult to get obtain varied footage

Researched more on other methods at the varioussteps.

Perhaps interest points moving in the same direction.