1. Stockman CSE/MSU Fall 2005 Models and Matching Methods of modeling objects and their environments; Methods of matching models to sensed data for recogniton

2. Stockman CSE/MSU Fall 2005 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. Stockman CSE/MSU Fall 2005 Models are what models do

4. Stockman CSE/MSU Fall 2005 What do models do?

5. Stockman CSE/MSU Fall 2005 Vertex-edge-face models Polyhedra and extensions

6. Stockman CSE/MSU Fall 2005 Vertex-Edge-Face model

7. Stockman CSE/MSU Fall 2005 Sample object All surfaces are planar or cylindrical

8. Stockman CSE/MSU Fall 2005 Matching methods Hypothesize point correspondences Filter on distances Compute 3D alignment of model to data Verify positions of other model points, edges, or faces LOTS of work in the literature on this! Can work for many industrial objects (and human faces perhaps!)

9. Stockman CSE/MSU Fall 2005 Triangular meshes

10. Stockman CSE/MSU Fall 2005 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.

11. Stockman CSE/MSU Fall 2005 Meshes are very general They are usually verbose and often are too detailed for many operations, but are often used in CAD

12. Stockman CSE/MSU Fall 2005 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. Stockman CSE/MSU Fall 2005 Mesh characteristics + can be easy to generate from scanned data

14. Stockman CSE/MSU Fall 2005 Making mesh models

15. Stockman CSE/MSU Fall 2005 Physics-based models Can be used to make meshes; Meshes retain perfect topology; Can span spots of bad or no data

16. Stockman CSE/MSU Fall 2005 Physics-based modeling

17. Stockman CSE/MSU Fall 2005 Forces move points on the model; halt at scanned data

18. Stockman CSE/MSU Fall 2005 Fitting an active contour to image data

19. Stockman CSE/MSU Fall 2005 Balloon model for closed object surface Courtesy of Chen and Medioni

20. Stockman CSE/MSU Fall 2005 Balloon evolution balloon stops at data points mesh forces constrain neighbors large triangles split into 4 triangles resulting mesh has correct topology

21. Stockman CSE/MSU Fall 2005 Physics-based models Can also model dynamic behavior of solids (Finite Element Methods)

22. Stockman CSE/MSU Fall 2005 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

23. Stockman CSE/MSU Fall 2005 Volume model: voxels, octrees

24. Stockman CSE/MSU Fall 2005 Simple object and its octree

25. Stockman CSE/MSU Fall 2005 Generalized cylinders

26. Stockman CSE/MSU Fall 2005 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

27. Stockman CSE/MSU Fall 2005 Extracting a model from a segmented image region Courtesy of Chen and Medioni

28. Stockman CSE/MSU Fall 2005 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?

29. Stockman CSE/MSU Fall 2005 Generalized cylinders

30. Stockman CSE/MSU Fall 2005 View class models Objects modeled by the distinct views that they can produce

31. Stockman CSE/MSU Fall 2005 “aspect model” of a cube

32. Stockman CSE/MSU Fall 2005 Recognition using an aspect model

33. Stockman CSE/MSU Fall 2005 View class model of chair 2D Graph-matching (as in Ch 11) used to evaluate match.

34. Stockman CSE/MSU Fall 2005 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.

35. Stockman CSE/MSU Fall 2005 Matching image edges to model limbs Could recognize car model at stoplight or gate.

36. Stockman CSE/MSU Fall 2005 Appearance-based models Using a basis of sub images; Using PCA to compress bases; Eigenfaces (see older.pdf slides 14C)

37. Stockman CSE/MSU Fall 2005 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.)

38. Stockman CSE/MSU Fall 2005 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, …