Kazuhiro Fukui

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This paper introduces a novel approach for face recognition using multiple face patterns obtained in various views for robot vision. A face pattern may change dramatically due to changes in the relation between the positions of a robot, a subject and light sources. As a robot is not generally able to ascertain such changes by itself, face recognition in(More)
In this paper, we propose a new image feature based on spatial co-occurrence among micropatterns, where each micropattern is represented by a Local Binary Pattern (LBP). In conventional LBP-based features such as LBP histograms, all the LBPs of micropatterns in the image are packed into a single histogram. Doing so discards important information concerning(More)
In this paper, we propose a novel method named the Multiple Constrained Mutual Subspace Method which increases the accuracy of face recognition by introducing a framework provided by ensemble learning. In our method we represent the set of patterns as a low-dimensional subspace, and calculate the similarity between an input subspace and a reference(More)
This paper presents a novel algorithm for estimating stereo disparity which exploits the benefit of learning to the fullest. Given a cost volume of stereo matching, we solve the cost aggregation and disparity computation in one shot by using a classifier; we design a feature called matching cost pattern for the input which we extract from the cost volume(More)
This paper proposes the kernel orthogonal mutual subspace method (KOMSM) for 3D object recognition. KOMSM is a kernel-based method for classifying sets of patterns such as video frames or multi-view images. It classifies objects based on the canonical angles between the nonlinear subspaces, which are generated from the image patterns of each object class by(More)
This paper introduces the kernel constrained mutual subspace method (KCMSM) and provides a new framework for 3D object recognition by applying it to multiple view images. KCMSM is a kernel method for classifying a set of patterns. An input pattern x is mapped into the high-dimensional feature space F via a nonlinear function φ, and the mapped pattern φ(x)(More)
Escherichia coli K-12 has the ability to migrate on semisolid media by means of swarming motility. A systematic and comprehensive collection of gene-disrupted E. coli K-12 mutants (the Keio collection) was used to identify the genes involved in the swarming motility of this bacterium. Of the 3,985 nonessential gene mutants, 294 were found to exhibit a(More)
In this paper, we propose a method for fast and accurate extraction of feature points such as pupils, nostrils, mouth edges, and the like from dynamic images with the purpose of face recognition. Accuracy of face extraction with these feature points used as criteria greatly affects the capabilities of face recognition methods based on pattern matching. This(More)