IATMLRP 2012 - Interactive and Adaptive Techniques for Machine Learning, Recognition and Perception

Human interaction is a very active field that is receiving increasing attention in the pattern recognition and machine learning community.
In this new paradigm the systems do not perform only in an automatic way but also in an interactive fashion.
The main reason for this is that automatic systems are not free from errors and, being high quality results the principal objective, a kind of supervision is needed. On the other hand, as time goes by, intrinsic interactive applications are more important and frequent.The use of the interactive paradigm in Pattern Recognition opens the door to new challenges in order to make convenient use of a number of emerging methods for supporting learning and data analysis in dynamics contexts: active and adaptive learning, hypothesis generation, data managed techniques, combining classifier techniques, probabilistic learning, interactive transduction, etc. Moreover, another challenge is the application of these ideas to interesting real-word tasks, as human behavior analysis, text transcription, content-based image retrieval, handwriting recognition, surveillance, biometric systems and many others.
This special session welcomes articles on advances on all the aforementioned hot topics.