Structured learning of metric ensembles with application to person re-identification

Matching individuals across non-overlapping camera networks, known as person re-identification, is a fundamentally challenging problem due to the large visual appearance changes caused by variations of viewpoints, lighting, and occlusion. Approaches in literature can be categoried into two streams: The first stream is to develop reliable features against realistic conditions by combining several visual features in a pre-defined way; the second stream is to learn a metric from training data to ensure strong inter-class differences and intra-class similarities. However, seeking an optimal combination of visual features which is generic yet adaptive to different benchmarks is a unsoved problem, and metric learning models easily get over-fitted due to the scarcity of training data in person re-identification. In this paper, we propose two effective structured learning based approaches which explore the adaptive effects of visual features in recognizing persons in different benchmark data sets. Our framework is built on the basis of multiple low-level visual features with an optimal ensemble of their metrics. We formulate two optimization algorithms, CMCtriplet and CMCstruct, which directly optimize evaluation measures commonly used in person re-identification, also known as the Cumulative Matching Characteristic (CMC) curve.Comment: 16 pages. Extended version of "Learning to Rank in Person Re-Identification With Metric Ensembles", at http://www.cv-foundation.org/openaccess/content_cvpr_2015/html/Paisitkriangkrai_Learning_to_Rank_2015_CVPR_paper.html. arXiv admin note: text overlap with arXiv:1503.0154

Fractal descriptors based on the probability dimension: a texture analysis and classification approach

In this work, we propose a novel technique for obtaining descriptors of gray-level texture images. The descriptors are provided by applying a multiscale transform to the fractal dimension of the image estimated through the probability (Voss) method. The effectiveness of the descriptors is verified in a classification task using benchmark over texture datasets. The results obtained demonstrate the efficiency of the proposed method as a tool for the description and discrimination of texture images.Comment: 7 pages, 6 figures. arXiv admin note: text overlap with arXiv:1205.282

Topological Surface States Protected From Backscattering by Chiral Spin Texture

Topological insulators are a new class of insulators in which a bulk gap for electronic excitations is generated by strong spin orbit coupling. These novel materials are distinguished from ordinary insulators by the presence of gapless metallic boundary states, akin to the chiral edge modes in quantum Hall systems, but with unconventional spin textures. Recently, experiments and theoretical efforts have provided strong evidence for both two- and three-dimensional topological insulators and their novel edge and surface states in semiconductor quantum well structures and several Bi-based compounds. A key characteristic of these spin-textured boundary states is their insensitivity to spin-independent scattering, which protects them from backscattering and localization. These chiral states are potentially useful for spin-based electronics, in which long spin coherence is critical, and also for quantum computing applications, where topological protection can enable fault-tolerant information processing. Here we use a scanning tunneling microscope (STM) to visualize the gapless surface states of the three-dimensional topological insulator BiSb and to examine their scattering behavior from disorder caused by random alloying in this compound. Combining STM and angle-resolved photoemission spectroscopy, we show that despite strong atomic scale disorder, backscattering between states of opposite momentum and opposite spin is absent. Our observation of spin-selective scattering demonstrates that the chiral nature of these states protects the spin of the carriers; they therefore have the potential to be used for coherent spin transport in spintronic devices.Comment: to be appear in Nature on August 9, 200

Edge structure of graphene monolayers in the {\nu} = 0 quantum Hall state

Monolayer graphene at neutrality in the quantum Hall regime has many competing ground states with various types of ordering. The outcome of this competition is modified by the presence of the sample boundaries. In this paper we use a Hartree-Fock treatment of the electronic correlations allowing for space-dependent ordering. The edge influence is modeled by a simple perturbative effective magnetic field in valley space. We find that all phases found in the bulk of the sample, ferromagnetic, canted antiferromagnetic, charge-density wave and Kekul$\'e$ distortion are smoothly connected to a Kekul$\'e$-distorted edge. The single-particle excitations are computed taking into account the spatial variation of the order parameters. An eventual metal-insulator transition as a function of the Zeeman energy is not simply related to the type of bulk order.Comment: 18 pages, 11 figures, corresponds to published versio

Isolated pairs of Majorana zero modes in a disordered superconducting lead monolayer

Majorana zero modes are fractional quantum excitations appearing in pairs, each pair being a building block for quantum computation . Some possible signatures of these excitations have been reported as zero bias peaks at endpoints of one-dimensional semiconducting wires and magnetic chains. However, 1D systems are by nature fragile to a small amount of disorder that induces low-energy excitations, hence obtaining Majorana zero modes well isolated in a hard gap requires extremely clean systems. Two-dimensional systems offer an alternative route to get robust Majorana zero modes. Indeed, it was shown recently that Pb/Co/Si(111) could be used as a platform for generating 2D topological superconductivity with a strong immunity to local disorder. While 2D systems exhibit dispersive chiral edge states, they can also host Majorana zero modes located on local topological defects. According to predictions, if an odd number of zero modes are located in a topological domain an additional zero mode should appear all around the domain's edge. Here we use scanning tunneling spectroscopy to characterize a disordered superconducting monolayer of Pb coupled to underlying Co-Si magnetic islands meant to induce a topological transition. We show that pairs of zero modes are stabilized: one zero mode positioned at a point in the middle of the magnetic domain and its zero mode partner extended all around the domain. The zero mode pair is remarkably robust, it is isolated within a hard superconducting energy gap and it appears totally immune to the strong disorder present in the Pb monolayer. Our theoretical scenario supports the protected Majorana nature of this zero mode pair, highlighting the role of magnetic or spin-orbit coupling textures. This robust pair of Majorana zero modes offers a new platform for theoretical and experimental study of quantum computing