IJCAI 2003 Toward Generic Model-based Object Recognition by Knowledge Acquisition and Machine Learning J.Kerr & P.Compton Speaker: Julian Kerr School of Computer Science and Engineering University of New South Wales Sydney, Australia

Artificial Vision Motivation Existing systems Generic solution?

Two level cognitive process –Subconscious –Conscious Biological Vision

Learning Directly –Tutor has language to express concept & pupil understands this language –Knowledge acquisition By example –Pupil forms its own hypothesis –Machine learning

Learning Texture by Example

Learning Directly 1

Define a grammar with which an expert can construct rules Grammar needs to be computable Learning Directly 2

Learning Directly 3

Learn Directly or by Example? Correction at each level has associated strengths and weaknesses. System can assist and limit selection of means of error correction.

Pixel Level Correction

Conclusions A method for interactive learning –By example –By direct knowledge acquisition Guarantees object-level consistency Generic within the bounds of pixel and object level feature spaces