ASEMINAR

ON

“CONCEPT OF STEREO VISION BASED VIRTUAL TOUCH SCREEN”

VIVEK R. CHAMORSHIKAR

WHAT IS STEREO VISION?

Stereo Vision is a by product of good binocular vision.

BINOCULAR: Involving both eyes at once.

BINOCULAR VISION: Here both eyes aim simultaneously at the same visual target, vision in which both eyes work together as a coordinated team equally and accurately.

STEREO VISION:(stereopsis or stereoscopic vision) Vision in which two separate images from two eyes are successfully combined into one image in the brain.

How it works?

Why to use Stereo Vision?

Stereo Vision is related to stereopsis.

Stereopsis (stereo means “three-dimensional” or “solid”

and opsis means “sight” or “view”).

Basic Ability of Stereo Vision: The ability to infer

information on the 3-D structure and distance of a scene

from two or more images taken from two different

viewpoints.

Stereo vision is most cost efficient way, instead of using

the costly sensors.

Requirements for the system are as-

1. Mouse input should be replaced by touch input. Create active/inactive spaces for interactions.

2. GUI applications should be designed to enable touch input events.

Fig 1. Figure showing the efforts faced between human and machine interaction.

3. Two cameras are needed. It helps to distinguish interactive parts of captured image .Accurate and reliable 3-D image is captured.Accurate dimensions are calculated.

4. Synchronization is needed by two cameras. The image frames should be captured from two cameras at

the same time and also frame rate of two cameras should be same.

5. Distance Calibration.The calibration of distance of blob (object used for input)

should be nearest to the actual distance of screen for good result.

PROBLEMS IN STEREO VISION

Problems to solve in stereo vision are:

1. Correspondence Problem

2. Calibration Problem

3. Synchronization Problem

4. Shadow Problem

5. Sunlight Problem

SOLUTION FOR CORRESPONDENCE PROBLEM

Two algorithms to solve correspondences problem

Correlation-based Algorithm- Checking if one location in

one image looks/seems like another in another image.

Produce a DENSE set of correspondences.

Feature-based Algorithm - Finding features in the image

and seeing if the layout of a subset of features is similar in

the two images.

Produce a SPARSE set of correspondences.

APPLICATIONS OF STEREO VISION 1.People Tracking

2.Robotics

3.Random Bin Picking (RBP)

4.Surgeries

5.3-D Underwater Mosaicking

Stereo Vision has many Other Applications:   Driver assistance system Forensics - Crime Scenes, Traffic Accidents Mining - Mine face measurement Civil Engineering - Structure monitoring Collision Avoidance Manufacturing- Process Monitoring

ADVANATAGES AND DISADVANTAGES OF STEREO VISION

Advantages of Stereo Vision:

1. Robustness

2. Gives a very dense depth (or range) map.

3. Use to calculate shape of objects.

4. Human motion detection is possible instead of using sensors for it.

Disadvantages of Stereo Vision:

1. The system must be pre-calibrated.

2. Has to be used in indoor environment

3. Shadow and sunlight present in the experimental area makes difficult in distance calculation.

Tracking of Blob:

Novel algorithm is used for efficient motion detection and

calculating distance of blob.

Combining Blob:

After assigning all the labels to every pixel of the image we count all

the labels other than background labels (i.e. other than 0) and store its

corresponding (x, y) coordinates. The pixels having same label is

considered as a single object and a box is drawn around it using the

maximum and minimum x and y coordinates. Height Map:

In computer graphics, heightmap  is a image used to store values,

such as surface elevation data, for display in 3D Computer graphics.

STEREO RANGING: Calculating the distance to objects by making a pair of

observations at different locations.

Range = (Focal length x Camera baseline) / Disparity

C0 - Left CameraC1 -Right CameraP -Observed feature pointF -focal lengthB -baseline distanceD -distance to observed feature pointc0, c1 -Pixel center of camera imagesv0, p1 -pixel position of observed feature pointv0, v1 -Pixel displacement of observed feature pointDisparity (D) = v1-v0Distance (D) = bf/d

UNCERTAINTY PROBLEM: Since there is uncertainty associated with the disparity

measurement.

CONCLUSION

Stereo vision

Applications

Requirements for the system to use stereo vision.

Advantages and Disadvantages of stereo vision.

The calculation of the distance of the blob from

two cameras.

Thank You….