computer vision - suraj @ lumssuraj.lums.edu.pk/~cs101a06/lectures/computer vision.pdf1 computer...
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Computer VisionComputer VisionCS101: Wk 08 Topical LectureCS101: Wk 08 Topical Lecture
What is Computer VisionWhat is Computer Vision
““The goal of Computer Vision is to make The goal of Computer Vision is to make useful decisions about real physical useful decisions about real physical objects and scenes based on sensed objects and scenes based on sensed imagesimages””Image and Video Image and Video UnderstandingUnderstandingMIT Copy DemoMIT Copy Demo
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Computer Vision
Image IN
Symbolic Decision or ModelOUT
ComputerGraphics
Model IN Image OUT
Relationship between Computer Relationship between Computer Graphics and Computer VisionGraphics and Computer Vision
Writing a Program to Detect FacesWriting a Program to Detect Faces
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Face DetectionFace DetectionWhat is a What is a (human) face?(human) face?
Your Your description description should be should be invariant to invariant to 3D rotation, 3D rotation, illumination, illumination, facial facial expressionexpression
Viola/Jones Face Detector (2001): Using implementation in OpenCV
Results of Schneiderman/Kanade Face Detector
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Taxonomy of Vision ProblemsTaxonomy of Vision Problems
1.1. Reconstruction:Reconstruction:–– estimate parameters of external 3D world.estimate parameters of external 3D world.
2.2. Segmentation and Tracking:Segmentation and Tracking:–– partition partition I(x,y,tI(x,y,t) into subsets of separate objects.) into subsets of separate objects.–– Given an object in Given an object in I(x,y,tI(x,y,t), find the same object in I(x,y,t+1)), find the same object in I(x,y,t+1)
3.3. Recognition:Recognition:–– action recognition: activity, gesture, expressionaction recognition: activity, gesture, expression–– face recognitionface recognition–– object recognitionobject recognition
Ref: Jitendra Malik, UCB
1. Reconstruction1. Reconstruction
To recover 3D geometric models from To recover 3D geometric models from images or videoimages or video
Inverse Problem of Computer GraphicsInverse Problem of Computer Graphics
Shape from XShape from X–– Shading, Motion, StereoShading, Motion, Stereo
Video simplifies the problemVideo simplifies the problemOptimization Optimization problemproblem
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Path Planning for Biped RobotsPath Planning for Biped Robotshttp://http://www.cs.cmu.edu/~Joel/footstep/pictures.html#planswww.cs.cmu.edu/~Joel/footstep/pictures.html#plans
Ref: Tsai and Shah, UCF
Shape From Shading
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Reconstruction from Old PaintingsReconstruction from Old Paintings
Reconstruction: Reconstruction: Recovering Camera TransformationRecovering Camera Transformation
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RegistrationRegistration
Reference Image
Aerial Image
Qs: Where was the camera when aerialimage was taken
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2. Segmentation and Tracking2. Segmentation and Tracking
SegmentationSegmentation–– Going from Images to ObjectsGoing from Images to Objects
IllIll--posed problemposed problem
Hard to define clearlyHard to define clearly……What is meant by an object?What is meant by an object?
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•Manual segmentations by different people are also not the same•Transparency effects are not taken into account
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TrackingTracking
Given an Object in Frame Given an Object in Frame tt, find that , find that object in frame object in frame tt+1+1
Ref: Khurram Shafique, Alper Yilmaz, Mubarak Shah, UCF
RecognitionRecognition
Activity RecognitionActivity RecognitionFace RecognitionFace RecognitionGender RecognitionGender Recognition