On Comprehensive Visual Learning

1 Comprehensive visual learning is the treatment of theories and techniques for computer vision systems to automatically learn to understand comprehensive visual information with minimal human-imposed rules about the visual world. This article discusses some major performance diiculties encountered by currently prevailing approaches to computer vision and introduces the promising direction of comprehensive learning towards overcoming these diiculties. It also indicates why the direction may have a profound impact on the performance of computer vision algorithms for real world problems. Some example techniques for comprehensive visual learning are presented.

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