Incremental pairwise discriminant analysis based visual tracking

The distinguishment between the object appearance and the background is the useful cues available for visual tracking in which the discriminant analysis is widely applied However due to the diversity of the background observation there are not adequate negative samples from the background which usually lead the discriminant method to tracking failure Thus a natural solution is to construct an object-background pair constrained by the spatial structure which could not only reduce the neg-sample number but also make full use of the background information surrounding the object However this Idea is threatened by the variant of both the object appearance and the spatial-constrained background observation especially when the background shifts as the moving of the object Thus an Incremental pairwise discriminant subspace is constructed in this paper to delineate the variant of the distinguishment In order to maintain the correct the ability of correctly describing the subspace we enforce two novel constraints for the optimal adaptation (1) pairwise data discriminant constraint and (2) subspace smoothness The experimental results demonstrate that the proposed approach can alleviate adaptation drift and achieve better visual tracking results for a large variety of nonstationary scenes (C) 2010 Elsevier B V All rights reserved

Relaxation of selective constraints on avian mitochondrial DNA following the degeneration of flight ability

The evolution of flight is the most important feature of birds, and this ability has helped them become one of the most successful groups of vertebrates. However, some species have independently lost their ability to fly. The degeneration of flight abilit

Variation patterns of the mitochondrial 16S rRNA gene with secondary structure constraints and their application to phylogeny of cyprinine fishes (Teleostei : Cypriniformes)

The mitochondrial 16S ribosomal RNA (rRNA) gene sequences from 93 cyprinid fishes were examined to reconstruct the phylogenetic relationships within the diverse and economically important subfamily Cyprininae. Within the subfamily a biased nucleotide composition (A > T, C > G) was observed in the loop regions of the gene, and in stem regions apparent selective pressures of base pairing showed a bias in favor of G over C and T over A. The bias may be associated with transition-transversion bias. Rates of nucleotide substitution were lower in stems than in loops. Analysis of compensatory substitutions across these taxa demonstrates 68% covariation in the gene and a logical weighting factor to account for dependence in mutations for phylogenetic inference should be 0.66. Comparisons of varied stem-loop weighting schemes indicate that the down-weightings for stem regions could improve the phylogenetic analysis and the degree of non-independence of stem substitutions was not as important as expected. Bayesian inference under four models of nucleotide substitution indicated that likelihood-based phylogenetic analyses were more effective in improving the phylogenetic performance than was weighted parsimony analysis. In Bayesian analyses, the resolution of phylogenies under the 16-state models for paired regions, incorporating GTR + G + I models for unpaired regions was better than those under other models. The subfamily Cyprininae was resolved as a monophyletic group, as well as tribe Labein and several genera. However, the monophyly of the currently recognized tribes, such as Schizothoracin, Barbin, Cyprinion + Onychostoma lineages, and some genera was rejected. Furthermore, comparisons of the parsimony and Bayesian analyses and results of variable length bootstrap analysis indicates that the mitochondrial 16S rRNA gene should contain important character variation to recover well-supported phylogeny of cyprinid taxa whose divergences occurred within the recent 8 MY, but could not provide resolution power for deep phylogenies spanning 10-19 MYA. (c) 2008 Published by Elsevier Inc.

delegation model for periodicity constraints-based dac

Xidian University