Finding Faces in Cluttered Scenes using Random Labeled Graph Matching

An algorithm for locating quasi-frontal views of human faces in cluttered scenes is presented. The algorithm works by coupling a set of local feature detectors with a statistical model of the mutual distances between facial features it is invariant with respect to translation, rotation (in the plane), and scale and can handle partial occlusions of the face. On a challenging database with complicated and varied backgrounds, the algorithm achieved a correct localization rate of 95% in images where the face appeared quasi-frontally

Influence of Zn excess on compositional, structural and vibrational properties of Cu2ZnSn0.5Ge0.5Se4 thin films and their effect on solar cell efficiency

This Accepted Manuscript will be available for reuse under a CC BY-NC-ND licence after 24 months of embargo periodThe effect of Zn content on compositional, structural and vibrational properties of Cu2ZnSn1-xGexSe4 (CZTGSe, x ~ 0.5) thin films is studied. Kesterite layer is deposited by co-evaporation onto 5 × 5 cm2 Mo/SLG substrate followed by a thermal treatment at maximum temperature of 480 °C, obtaining areas with different composition and morphology which are due to the sample position in the co-evaporation system and to the non-uniform temperature distribution across the substrate. Kesterite layers with higher Zn amounts are characterized by lower Cu and Ge contents; however, a uniform Ge distribution through the absorber layer is detected in all cases. The excess Zn concentration leads to the formation of ZnSe secondary phase on the surface and in the bulk of the absorber as determined by Raman spectroscopy. When higher Ge content and no ZnSe are present in the absorber layer, a compact structure is formed with larger grain size of kesterite. This effect could explain the higher Voc of the solar cell. The Zn content does not affect the bandgap energy significantly (Eg near 1.3 eV), although the observed effect of Zn excess in CZTGSe results in a decreased device performance from 6.4 to 4.2%. This investigation reveals the importance of the control of the off-stoichiometric CZTGSe composition during the deposition process to enhance solar cells propertiesThis work was supported by Spanish Ministry of Science, Innovation and Universities Project WINCOST (ENE2016-80788-C5-2-R) and European Project INFINITE CELL (H2020-MSCA-RISE-2017-777968). ARP also acknowledges financial support from Community of Madrid within Youth Employment Program (PEJD-2017-PRE/IND-4062). MG acknowledges the financial support from ACCIÓ-Generalitat de Catalunya within the TECNIOspring Plus fellowship (TECSPR18-1-0048

Face Localization via Shape Statistics

In this paper, a face localization system is proposed in which local detectors are coupled with a statistical model of the spatial arrangement of facial features to yield robust performance. The outputs from the local detectors are treated as candidate locations and constellations are formed from these. The effects of translation, rotation, and scale are eliminated by mapping to a set of shape variables. The constellations are then ranked according to the likelihood that the shape variables correspond to a face versus an alternative model. Incomplete constellations, which occur when some of the true features are missed, are handled in a principled way

Routes to develop a [S]/([S]+[Se]) gradient in wide band-gap Cu2ZnGe(S,Se)4 thin-film solar cells

Wide band-gap kesterite-based solar cells are very attractive to be used for tandem devices as well as for semi-transparent photovoltaic cells. Here, Cu2ZnGe(S,Se)4 (CZGSSe) thin films have been grown by sulfurization of co-evaporated Cu2ZnGeSe4. The influence of a NaF precursor layer and of a Se capping film on CZGSSe absorbers and solar cells has been investigated. It has been found that the distribution of [S]/([S]+[Se]) through the CZGSSe absorber layer is strongly dependent on the Na content. Na promotes the diffusion of S towards the bulk of the absorber layer. Thicker NaF layers>6 nm lead to a higher S content in the bulk of the absorber layer, but to a decreased accumulation of sulphur at the surface, as detected by GIXRD, GD-OES, and Raman spectroscopy measurements. A relationship between Jsc, FF and Na-content supplied was found; higher Na content resulted in improved solar cell efficiencies. It has also been possible to modify the [S]/([S]+[Se])-gradient throughout the CZGSSe film by the absence of the Se capping layer, achieving devices with 2.7% performance and Eg = 2.0 eV. This work reveals two ways to control the [S]/([S]+[Se]) depth-profile to produce wide band gap CZGSSe absorber layers for efficient solar cells

Behavioral Responses to a Repetitive Visual Threat Stimulus Express a Persistent State of Defensive Arousal in Drosophila

The neural circuit mechanisms underlying emotion states remain poorly understood. Drosophila offers powerful genetic approaches for dissecting neural circuit function, but whether flies exhibit emotion-like behaviors has not been clear. We recently proposed that model organisms may express internal states displaying “emotion primitives,” which are general characteristics common to different emotions, rather than specific anthropomorphic emotions such as “fear” or “anxiety.” These emotion primitives include scalability, persistence, valence, and generalization to multiple contexts. Here, we have applied this approach to determine whether flies’ defensive responses to moving overhead translational stimuli (“shadows”) are purely reflexive or may express underlying emotion states. We describe a new behavioral assay in which flies confined in an enclosed arena are repeatedly exposed to an overhead translational stimulus. Repetitive stimuli promoted graded (scalable) and persistent increases in locomotor velocity and hopping, and occasional freezing. The stimulus also dispersed feeding flies from a food resource, suggesting both negative valence and context generalization. Strikingly, there was a significant delay before the flies returned to the food following stimulus-induced dispersal, suggestive of a slowly decaying internal defensive state. The length of this delay was increased when more stimuli were delivered for initial dispersal. These responses can be mathematically modeled by assuming an internal state that behaves as a leaky integrator of stimulus exposure. Our results suggest that flies’ responses to repetitive visual threat stimuli express an internal state exhibiting canonical emotion primitives, possibly analogous to fear in mammals. The mechanistic basis of this state can now be investigated in a genetically tractable insect species

General Adaptive Neighborhood Image Restoration, Enhancement and Segmentation

12 pagesInternational audienceThis paper aims to outline the General Adaptive Neighborhood Image Processing (GANIP) approach [1–3], which has been recently introduced. An intensity image is represented with a set of local neighborhoods defined for each point of the image to be studied. These so-called General Adaptive Neighborhoods (GANs) are simultaneously adaptive with the spatial structures, the analyzing scales and the physical settings of the image to be addressed and/or the human visual system. After a brief theoretical introductory survey, the GANIP approach will be successfully applied on real application examples in image restoration, enhancement and segmentation

3D Brain Segmentation Using Dual-Front Active Contours with Optional User Interaction

Important attributes of 3D brain cortex segmentation algorithms include robustness, accuracy, computational efficiency, and facilitation of user interaction, yet few algorithms incorporate all of these traits. Manual segmentation is highly accurate but tedious and laborious. Most automatic techniques, while less demanding on the user, are much less accurate. It would be useful to employ a fast automatic segmentation procedure to do most of the work but still allow an expert user to interactively guide the segmentation to ensure an accurate final result. We propose a novel 3D brain cortex segmentation procedure utilizing dual-front active contours which minimize image-based energies in a manner that yields flexibly global minimizers based on active regions. Region-based information and boundary-based information may be combined flexibly in the evolution potentials for accurate segmentation results. The resulting scheme is not only more robust but much faster and allows the user to guide the final segmentation through simple mouse clicks which add extra seed points. Due to the flexibly global nature of the dual-front evolution model, single mouse clicks yield corrections to the segmentation that extend far beyond their initial locations, thus minimizing the user effort. Results on 15 simulated and 20 real 3D brain images demonstrate the robustness, accuracy, and speed of our scheme compared with other methods

Quantum monitoring of cellular metabolic activities in single mitochondria

Free radicals play a vital role in all kinds of biological processes including immune responses. However, free radicals have short lifetimes and are highly reactive, making them difficult to measure using current methods. Here, we demonstrate that relaxometry measurement, or T1, inherited from the field of diamond magnetometry can be used to detect free radicals in living cells with subcellular resolution. This quantum sensing technique is based on defects in diamond, which convert a magnetic signal into an optical signal, allowing nanoscale magnetic resonance measurements. We functionalized fluorescent nanodiamonds (FNDs) to target single mitochondria within macrophage cells to detect the metabolic activity. In addition, we performed measurements on single isolated mitochondria. We were able to detect free radicals generated by individual mitochondria in either living cells or isolated mitochondria after stimulation or inhibition

Adaptive structure tensors and their applications

The structure tensor, also known as second moment matrix or Förstner interest operator, is a very popular tool in image processing. Its purpose is the estimation of orientation and the local analysis of structure in general. It is based on the integration of data from a local neighborhood. Normally, this neighborhood is defined by a Gaussian window function and the structure tensor is computed by the weighted sum within this window. Some recently proposed methods, however, adapt the computation of the structure tensor to the image data. There are several ways how to do that. This article wants to give an overview of the different approaches, whereas the focus lies on the methods based on robust statistics and nonlinear diffusion. Furthermore, the dataadaptive structure tensors are evaluated in some applications. Here the main focus lies on optic flow estimation, but also texture analysis and corner detection are considered