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# Models and Matching

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### Transcript

• 1. Models and Matching Methods of modeling objects and their environments; Methods of matching models to sensed data for recogniton
• 2. Some methods to study
• Mesh models ( surface )
• Vertex-edge-face models ( surface )
• Functional forms: superquadrics ( surface )
• Generalized cylinders ( volume )
• Voxel sets and octrees ( volume )
• View class models ( image-based )
• Recognition by appearance ( image-based )
• Functional models and the Theory of affordances ( object-oriented )
• 3. Models are what models do
• 4. What do models do?
• 5. Vertex-edge-face models Polyhedra and extensions; Model the surface of objects
• 6. Vertex-Edge-Face model
• 7. Sample object All surfaces are planar or cylindrical
• 8. Matching methods
• Hypothesize point correspondences
• Filter on distances
• Compute 3D alignment of model to data
• Verify positions of other model points, edges, or faces. You can now do this!
• LOTS of work in the literature on this! Can work for many industrial objects (and human faces perhaps!)
• 9. Triangular meshes Very general and used by most CAD systems.
• 10. Texture-mapped mesh dog Courtesy of Kari Puli With each triangle is a mapping of its vertices into pixels [r, c] of a color image. Thus any point of any triangle can be assigned a color [R, G, B]. There may be several images available to create these mappings. 3D SURFACE MODEL SURFACE PLUS TEXTURE
• 11. Meshes are very general They are usually verbose and often are too detailed for many operations, but are often used in CAD. (Volumetric cube models are actually displayed here: made from many views by Kari Pulli.)
• 12. Modeling the human body for clothing industry and … Multiple Structured light scanners used: could this be a service industry such as Kinkos? Actually cross sections of a generalized cylinder model.
• 13. Mesh characteristics + can be easy to generate from scanned data
• 14. Making mesh models
• 15. Marching cubes http://www.exaflop.org/docs/marchcubes/ (James Sharman) &quot;Marching Cubes: A High Resolution 3D Surface Construction Algorithm&quot;, William E. Lorensen and Harvey E. Cline, Computer Graphics (Proceedings of SIGGRAPH '87), Vol. 21, No. 4, pp. 163-169. Raster scan through image F(r, c). Look for adjacent pixels, one above threshold and one below threshold. Interpolate real coordinates for f(x, y) = t in between
• 16. Marching in 3D space F(s, r, c) Some voxel corners are above threshold t and some are below.
• 17. PhD work by Paul Albee 2004
• Used Argonne National Labs scanner
• High energy, high resolution planar Xrays penetrate object rotating on a turntable
• Computer aided tomography synthesizes a 3D volume of densities with voxel size of about 5 microns
• 18. Segmentation of Scutigera a tiny crablike organism Slice j of material density F( sj, r, c ) “ thresholded” volume
• 19. Some common 3D problems
• analyze blood vessel structure in head
• capture structure and motion of vertebrae
• of spine
• analyze porosity and structure of soil
• analyze structure of materials
• automatic segmentation into regions
• automatic correspondence of 3D points at
• two instants of of time
• 3D volume visualization and virtual tours
• 20. Scanning technique abstraction CCD camera (row) material sample X-ray planes scintillator Pin head rotate X-rays partly absorbed by sample; excite scintillator producing one row in the camera image; rotate sample a few degrees and produce another row; 3D reconstruction using CT
• 21. Scutigera: a tiny crustacean
• organism is smaller than 1 mm
• scanned at Argonne
• volume segmented and
• meshed by Paul Albee
• roughly ten million triangles
• to represent the surface
• anaglyph created for 3D
• visualization
• (view with stereo glasses)
• 22. Presentation of Results to User
• Can explore the 3D data using rotation/translation
• Can create stereo images from 3D data
• 23. Physics-based models Can be used to make meshes; Meshes retain perfect topology; Can span spots of bad or no data
• 24. Physics-based modeling
• 25. Forces move points on the model; halt at scanned data
• 26. Fitting an active contour to image data
• 27. Balloon model for closed object surface Courtesy of Chen and Medioni
• 28. Balloon evolution
• balloon stops at data points
• mesh forces constrain neighbors
• large triangles split into 4 triangles
• resulting mesh has correct topology
• hard CS part is detecting when balloon should be stopped by data point
• 29. Physics-based models Can also model dynamic behavior of solids (Finite Element Methods)
• 30. Tagged MRI: 3D interest points can be written to body! The MRI sensor tags living tissue and can sense its movement. Motion of a 3D tetrahedral finite elements model can then be analyzed. FMA model attempts to model the real physics of the heart. Work by Jinah Park and Dimitry Metaxes.
• 31. Algorithms from computer graphics make mesh models from blobs
• Marching squares applied to some connected image region (blob)
• Marching cubes applied to some connected set of voxels (blob)
• See a CG text for algorithms: see the visualization toolkit for software
• 32. The octree for compression
• 33. Generalized cylinders
• 34. Generalized cylinders
• component parts have axis
• cross section function describes variation along axis
• good for articulated objects, such as animals, tools
• can be extracted from intensity images with difficulty
• 35. Extracting a model from a segmented image region Courtesy of Chen and Medioni
• 36. Interpreting frames from video
• Can we match a frame region to a model?
• What about a sequence of frames?
• Can we determine what actions the body is doing?
• 37. Generalized cylinders
• 38. View class models Objects modeled by the distinct views that they can produce
• 39. “aspect model” of a cube
• 40. Recognition using an aspect model
• 41. View class model of chair 2D Graph-matching (as in Ch 11) used to evaluate match.
• 42. Side view classes of Ford Taurus (Chen and Stockman) These were made in the PRIP Lab from a scale model. Viewpoints in between can be generated from x and y curvature stored on boundary. Viewpoints matched to real image boundaries via optimization.
• 43. Matching image edges to model limbs Could recognize car model at stoplight or gate or in car wash.
• 44. Appearance-based models Using a basis of sub images; Using PCA to compress bases; Eigenfaces ( see older .pdf slides 14C)
• 45. Function-based modeling Object-oriented; What parts does the object have; What behaviors does it have; What can be done with it? (See plastic slides of Louise Starks’s work.)
• 46. Louise Stark: chair model
• Dozens of CAD models of chairs
• Program analyzes model for
• * stable pose
• * seat of right size
• * height off ground right size
• * no obstruction to body on seat
• * program would accept a trash can
• (which could also pass as a container)
• 47. Theory of affordances: J.J. Gibson
• An object can be “sittable”: a large number of chair types, a box of certain size, a trash can turned over, …
• An object can be “walkable”: the floor, ground, thick ice, bridge, ...
• An object can be a “container”: a cup, a hat, a barrel, a box, …
• An object can be “throwable”: a ball, a book, a coin, an apple, a small chair, …
• 48. Minski’s theory of frames (Schank’s theory of scripts)
• Frames are learned expectations – frame for a room, a car, a party, an argument, …
• Frame is evoked by current situation – how? (hard)
• Human “fills in” the details of the current frame (easier)
• 49. Make a frame for my house
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