1. Last week... why object recognition is difficult, the template model the feature recognition model, word recognition as a case study Today... Recognition of 3-d objects Recognition of faces Attention

2. Object Recognition How are 3-dimensional objects recognized?

3. Feature Theory: problems Relationships between features: = 1 line 1 half-circle These 3 letters share the same set of features… how are they distinguished by the visual system?

4. A theory is needed that consider the spatial relationships between the features of an object...

5. Recognition-by-Components Irv Biederman

6. Recognition-by-Components 36 Geons (Geometric Ions)

9. Non-Accidental Features Visual features that are evident regardless of the observer’s viewpoint.

10. Each geon has non-accidental features: –features that you can always see b/c they don’t change in different orientations –co-terminating lines can be seen to coterminate regardless of where the observer is. – straight lines always look straight

12. RBC: Matching process 1 - detect elementary features, edges 2 - find non-accidental properties 3 - determine component geons and their spatial relationships 4 - match to memory

13. RBC: evidence Partial or Degraded objects Object complexity Unusual orientations

16. RBC: evidence Partial or Degraded objects Object complexity Unusual orientations

18. RBC: evidence Partial or Degraded objects Object complexity Unusual orientations

21. RBC: problems Similar objects

23. RBC: problems Similar objects… faces, animals and other natural objects are hard to specify with geons RBC is pretty much a bottom-up model of object recognition. Top-down effects have not yet been addressed. View-point independent

24. A possibility: Maybe there are multiple types of objects recognition, and RBC is good for one of them. That is, perhaps models like RBC are good for pattern recognition cases where simple features are extracted and structural models are constructed from those features. Another type of object recognition might involve a more holistic or configural coding of object features. This system would be important for situations where objects were not easily broken down into individual features. Examples of this kind of object: faces, animals...