Trinocular stereovision using figural continuity, dealing with curved objects

A method to build a dense and reliable 3-D description of a scene from three digital images by means of passive stereovision is presented. This method uses figural continuity to improve the results of a previously developed algorithm. In particular, it copes much better with curved objects and produces results which are organized as 3-D chains of segments

Small-scale opencast mining: an important research field for anthropogenic geomorphology

Artisanal and small-scale mining (A&SM) is a growing economic sector in many third-world countries. This review focuses on anthropo-geomorphic factors and processes associated with small-scale opencast mining (SSOM), a form of A&SM in which near-surface ores are extracted by removing relatively thin covers of soil, bedrock or sediments. Being widespread and commonly conducted without proper planning and beyond the control of local authorities, this form of mining has potentially large impacts on landforms and landscape dynamics, often resulting in drastic consequences for the local environment and agriculture. SSOM should be regarded as a component of anthropogenic geomorphology because it involves the role of humans in creating landforms and modifying the operation of natural geomorphological processes, such as weathering, erosion, transport and deposition. By initiating new and modifying natural geomorphic processes, SSOM causes and/or accelerates geomorphic processes, resulting in various forms of land degradation. While the direct geomorphic impact of SSOM is in general easily discernible and leads to characteristic features, such as excavated pits and overburden spoil heaps, many secondary impacts are attributed to geomorphic processes triggered in the wake of the primary mining-induced landscape alterations. The magnitude of such secondary implications may well extend beyond the actual mining areas, but these effects have not been thoroughly addressed in the research so far. This review summarizes the known studies on the geomorphic impacts of SSOM operations and highlights common geomorphic processes and landforms associated with this type of anthropogenic activity, thus establishing a starting point for further in-depth research

Why Don't People Insure Late Life Consumption? A Framing Explanation of the Under-Annuitization Puzzle

Economic

Facing the music or burying our heads in the sand?: Adaptive emotion regulation in mid- and late-life

Psychological defense theories postulate that keeping threatening information out of awareness brings short-term reduction of anxiety at the cost of longer-term dysfunction. By contrast, Socioemotional Selectivity Theory suggests that preference for positively-valenced information is a manifestation of adaptive emotion regulation in later life. Using six decades of longitudinal data on 61 men, we examined links between emotion regulation indices informed by these distinct conceptualizations: defense patterns in earlier adulthood and selective memory for positively-valenced images in late life. Men who used more avoidant defenses in midlife recognized fewer emotionally-valenced and neutral images in a memory test 35-40 years later. Late-life satisfaction was positively linked with mid-life engaging defenses but negatively linked at the trend level with concurrent positivity bias

A polymer physics view on universal and sequence-specific aspects of chromosome folding

International audienc

Grid Loss: Detecting Occluded Faces

Detection of partially occluded objects is a challenging computer vision problem. Standard Convolutional Neural Network (CNN) detectors fail if parts of the detection window are occluded, since not every sub-part of the window is discriminative on its own. To address this issue, we propose a novel loss layer for CNNs, named grid loss, which minimizes the error rate on sub-blocks of a convolution layer independently rather than over the whole feature map. This results in parts being more discriminative on their own, enabling the detector to recover if the detection window is partially occluded. By mapping our loss layer back to a regular fully connected layer, no additional computational cost is incurred at runtime compared to standard CNNs. We demonstrate our method for face detection on several public face detection benchmarks and show that our method outperforms regular CNNs, is suitable for realtime applications and achieves state-of-the-art performance.Comment: accepted to ECCV 201

Multi-view Face Detection Using Deep Convolutional Neural Networks

In this paper we consider the problem of multi-view face detection. While there has been significant research on this problem, current state-of-the-art approaches for this task require annotation of facial landmarks, e.g. TSM [25], or annotation of face poses [28, 22]. They also require training dozens of models to fully capture faces in all orientations, e.g. 22 models in HeadHunter method [22]. In this paper we propose Deep Dense Face Detector (DDFD), a method that does not require pose/landmark annotation and is able to detect faces in a wide range of orientations using a single model based on deep convolutional neural networks. The proposed method has minimal complexity; unlike other recent deep learning object detection methods [9], it does not require additional components such as segmentation, bounding-box regression, or SVM classifiers. Furthermore, we analyzed scores of the proposed face detector for faces in different orientations and found that 1) the proposed method is able to detect faces from different angles and can handle occlusion to some extent, 2) there seems to be a correlation between dis- tribution of positive examples in the training set and scores of the proposed face detector. The latter suggests that the proposed methods performance can be further improved by using better sampling strategies and more sophisticated data augmentation techniques. Evaluations on popular face detection benchmark datasets show that our single-model face detector algorithm has similar or better performance compared to the previous methods, which are more complex and require annotations of either different poses or facial landmarks.Comment: in International Conference on Multimedia Retrieval 2015 (ICMR

Face reconstruction through active stereovision

The automatic face recognition is a very attractive problem and several solutions can be found in the literature . Most of them rely on the analysis of the images acquired by a classical CCD camera. These images are treated and given us input to a discrimination algorithm . However, the information contained in the image is relatively poor and it is very likely that these techniques will fail in the case of a large database with a lot of people . The surface of the faces is a very discriminant information so in this article, we propose a stereovision algorithm which can be used for the acquisition of the surface offaces . The problem of matching between the pattern and its images is solved using the epipolar constraint and the local coherency constraint . Some experimental results are shown .La reconnaissance automatique de visages est un problème qui suscite beaucoup d'intérêt et pour lequel divers algorithmes basés sur l'utilisation d'images acquises par des caméras CCD ont été proposés. L'information fournie aux algorithmes de discrimination mis en place dans ce type de solution est assez fruste et ces algorithmes sont peu susceptibles de fonctionner de manière robuste pour des bases comprenant un grand nombre d'individus. La surface du visage doit pouvoir être beaucoup plus discriminante. Dans cet article, nous proposons un algorithme de stéréovision active qui permet l'acquisition de surfaces de visages. Le problème de la mise en correspondance entre les éléments du motif projeté et leur image est résolu en utilisant la contrainte épipolaire et une contrainte de cohérence locale. Des résultats expérimentaux sont présentés

Gravitational and axial anomalies for generalized Euclidean Taub-NUT metrics

The gravitational anomalies are investigated for generalized Euclidean Taub-NUT metrics which admit hidden symmetries analogous to the Runge-Lenz vector of the Kepler-type problem. In order to evaluate the axial anomalies, the index of the Dirac operator for these metrics with the APS boundary condition is computed. The role of the Killing-Yano tensors is discussed for these two types of quantum anomalies.Comment: 23 page