Privacy-Protected Facial Biometric Verification via Fuzzy Forest Learning

Although visual surveillance has emerged as an effective technolody for public security, privacy has become an issue of great concern in the transmission and distribution of surveillance videos. For example, personal facial images should not be browsed without permission. To cope with this issue, face image scrambling has emerged as a simple solution for privacyrelated applications. Consequently, online facial biometric verification needs to be carried out in the scrambled domain thus bringing a new challenge to face classification. In this paper, we investigate face verification issues in the scrambled domain and propose a novel scheme to handle this challenge. In our proposed method, to make feature extraction from scrambled face images robust, a biased random subspace sampling scheme is applied to construct fuzzy decision trees from randomly selected features, and fuzzy forest decision using fuzzy memberships is then obtained from combining all fuzzy tree decisions. In our experiment, we first estimated the optimal parameters for the construction of the random forest, and then applied the optimized model to the benchmark tests using three publically available face datasets. The experimental results validated that our proposed scheme can robustly cope with the challenging tests in the scrambled domain, and achieved an improved accuracy over all tests, making our method a promising candidate for the emerging privacy-related facial biometric applications.

A recursive rule base adjustment algorithm for a fuzzy logic controller

This paper introduces a recursive rule base adjustment to enhance the performance of fuzzy logic controllers. Here the fuzzy controller is constructed on the basis of a decision table (DT), relying on membership functions and fuzzy rules that incorporate heuristic knowledge and operator experience. If the controller performance is not satisfactory, it has previously been suggested that the rule base be altered by combined tuning of membership functions and controller scaling factors. The alternative approach proposed here entails alteration of the fuzzy rule base. The recursive rule base adjustment algorithm proposed in this paper has the benefit that it is computationally more efficient for the generation of a DT, and advantage for online realization. Simulation results are presented to support this thesis. (c) 2005 Elsevier B.V. All rights reserved.

Genomic organization, complex splicing pattern and expression of a human septin gene on chromosome 17q25.3

The Ov/Br septin gene, which is also a fusion partner of MLL in acute myeloid leukaemia, is a member of a family of novel GTP binding proteins that have been implicated in cytokinesis and exocytosis. In this study, we describe the genomic and transcriptional organization of this gene, detailing seventeen exons distributed over 240 kb of sequence. Extensive database analyses identified orthologous rodent cDNAs that corresponded to new, unidentified 5' splice variants of the Ov/Br septin gene, increasing the total number of such variants to six. We report that splicing events, occurring at non-canonical sites within the body of the 3' terminal exon, remove either 1801 bp or 1849 bp of non-coding sequence and facilitate access to a secondary open reading frame of 44 amino acids maintained near the end of the 3' UTR. These events constitute a novel coding arrangement and represent the first report of such a design being implemented by a eukaryotic gene. The various Ov/Br proteins either differ minimally at their amino and carboxy termini or are equivalent to truncated versions of larger isoforms. Northern analysis with an Ov/Br septin 3' UTR probe reveals three transcripts of 4.4, 4 and 3 kb, the latter being restricted to a sub-set of the tissues tested. Investigation of the identified Ov/Br septin isoforms by RT-PCR confirms a complex transcriptional pattern, with several isoforms showing tissue-specific distribution. To date, none of the other human septins have demonstrated such transcriptional complexity.

Fuzzy Coding of Genetic Algorithms

A well-cited paper suggesting fuzzy coding as an alternative to the conventional binary, grey and floating-point representations used in genetic algorithms.