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Concept of stereo vision based virtual touch


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Concept of stereo vision based virtual touch

  2. 2. 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?
  3. 3. 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.
  4. 4. 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.
  5. 5. 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.
  6. 6. PROBLEMS IN STEREO VISIONProblems to solve in stereo vision are:1. Correspondence Problem2. Calibration Problem3. Synchronization Problem4. Shadow Problem5. Sunlight Problem
  7. 7. 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.
  8. 8. APPLICATIONS OF STEREO VISION1.People Tracking2.Robotics3.Random Bin Picking (RBP)4.Surgeries5.3-D Underwater MosaickingStereo 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
  9. 9. ADVANATAGES AND DISADVANTAGES OF STEREO VISION Advantages of Stereo Vision:1. Robustness2. 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 environment3. Shadow and sunlight present in the experimental area makes difficult in distance calculation.
  10. 10.  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.
  11. 11. 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 Camera C1 -Right Camera P -Observed feature point F -focal length B -baseline distance D -distance to observed feature point c0, c1 -Pixel center of camera images v0, p1 -pixel position of observed feature point v0, v1 -Pixel displacement of observed feature point Disparity (D) = v1-v0 Distance (D) = bf/d
  12. 12. UNCERTAINTY PROBLEM: Since there is uncertainty associated with the disparity measurement.
  13. 13. 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.
  14. 14. Thank You….