By Anil K. Jain, Martin H. C. Law (auth.), Sankar K. Pal, Sanghamitra Bandyopadhyay, Sambhunath Biswas (eds.)

This e-book constitutes the refereed court cases of the 1st overseas convention on trend reputation and computing device Intelligence, PReMI 2005, held in Kolkata, India in December 2005.

The 108 revised papers provided including 6 keynote talks and 14 invited papers have been rigorously reviewed and chosen from 250 submissions. The papers are equipped in topical sections on clustering, function choice and studying, class, neural networks and purposes, fuzzy good judgment and functions, optimization and illustration, photograph processing and research, video processing and machine imaginative and prescient, photograph retrieval and knowledge mining, bioinformatics program, net intelligence and genetic algorithms, in addition to tough units, case-based reasoning and data discovery.

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Extra resources for Pattern Recognition and Machine Intelligence: First International Conference, PReMI 2005, Kolkata, India, December 20-22, 2005. Proceedings

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Fifth Berkeley Symposium on Math. Stat. , University of California Press (1967) 281–297 10. : Finite Mixture Models. John Wiley & Sons, New York (2000) 11. : Pattern Classification. 2nd edn. John Wiley & Sons, New York (2001) 12. : Mean shift: A robust approach toward feature space analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (2002) 603–619 13. : An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 15 (1993) 1101–1113 14.

Fig. 5. 5 19 Activity Modeling and Anomaly Detection In the previous subsection, we described an approach for representing an activity as a sequence of shapes. But, when new activities are seen, then we need to develop approaches to detect these anomalous activities. The activity model under consideration is a continuous state HMM. An abnormal activity is defined as a change in the activity model, which could be slow or drastic and whose parameters are unknown. Drastic changes can be easily detected using the increase in tracking error or the negative log of the likelihood of current observation given past (OL).

In such systems again the problem of concept approximation and its role in reasoning about perceptions is one of the challenges nowadays. One should take into account that modeling complex phenomena entails the use of local models (captured by local agents, if one would like to use the multiagent terminology [20]) that should be fused afterwards. This process involves negotiations between agents [20] to resolve contradictions and conflicts in local modeling. This kind of modeling is becoming more and more important in dealing with complex real-life phenomena which we are unable to model using traditional analytical approaches.

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