Automatic fog detection and estimation of visibility distance through use of an onboard camera

In this paper, we will present a technique for measuring visibility distances under foggy weather conditions using a camera mounted onboard a moving vehicle. Our research has focused in particular on the problem of detecting daytime fog and estimating visibility distances; thanks to these efforts, an original method has been developed, tested and patented. The approach consists of dynamically implementing Koschmieder's law. Our method enables computing the meteorological visibility distance, a measure defined by the International Commission on Illumination (CIE) as the distance beyond which a black object of an appropriate dimension is perceived with a contrast of less than 5%. Our proposed solution is an original one, featuring the advantage of utilizing a single camera and necessitating the presence of just the road and sky in the scene. As opposed to other methods that require the explicit extraction of the road, this method offers fewer constraints by virtue of being applicable with no more than the extraction of a homogeneous surface containing a portion of the road and sky within the image. This image preprocessing also serves to identify the level of compatibility of the processed image with the set of Koschmieder's model hypotheses. Nicolas Hautiére graduated from the École Nationale des Travaux Publics de l'État, France (2002). He received his M.S. and Ph.D. degree in computer vision, respectively, in 2002 and 2005 from Saint-Étienne University (France). From 2002, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France. His research interests include trafic engineering, computer vision, and pattern recognition. Jean-Philippe Tarel graduated from the École Nationale des Ponts et Chaussées, Paris, France (1991). He received his Ph.D. degree in Applied Mathematics from Paris IX-Dauphine University in 1996 and he was with the Institut National de Recherche en Informatique et Automatique (INRIA) from 1991 to 1996. From 1997 to 1998, he was a research associate at Brown University, USA. From 1999, he is a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC), Paris, France, and from 2001 to 2003 in the INRIA. His research interests include computer vision, pattern recognition, and shape modeling. Jean Lavenant graduated from the École Nationale des Travaux Publics de l'État, Lyon, France (2001). He received the M.S. degree in Computer Vision from Jean Monnet university of Saint-Étienne in 2001. In 2001, he was a researcher in the Laboratoire Central des Ponts et Chaussées (LCPC). In 2002, he was a system engineer in Chicago (USA). He is currently an engineer for the french ministry of transports. Didier Aubert received the M.S. and Ph.D. degree, respectively, in 1985 and 1989 from the National Polytechnical Institut of Grenoble (INPG). From 1989--1990, he worked as a research scientist on the development of an automatic road following system for the NAVLAB at Carnegie Mellon University. From 1990–1994, he worked in the research department of a private company (ITMI). During this period he was the project leader of several projects dealing with computer vision. He is currently a researcher at INRETS since 1995 and works on Road traffic measurements, crowd monitoring, automated highway systems, and driving assistance systems for vehicles. He is an image processing expert for several companies, teaches at Universities (Paris VI, Paris XI, ENPC, ENST) and is at the editorial board of RTS (Research - Transport - Safety).     

Influence of the counter-ion on the effective charge of polyacrylic acid in dilute condition

Osmotic pressure measurements were satisfactorily used to compute the effective charge of poly(acrylic) acid (PAA) at different pHs and with different monovalent and divalent counterions. This experimental method is sensitive to the osmotically active species (polymer and counterions). After correction for the polymer contribution to the total osmotic pressure (solvency and excluded volume), the remaining pressure can be attributed to the polyelectrolyte counterions and processed with Donnan and equation of state in order to compute the effective charge number per polymeric chain (Z^eff). The behavior of Z^eff against the chain concentration and pH was investigated after neutralization of PAA with LiOH, NaOH, and TMAOH. The results clearly indicate that the nature of the monovalent counterion has no effect on Z^eff leading to the conclusion that the interaction between monovalent counterions and the acrylate functionality is purely electrostatic in agreement with conductimetric and potentiometric results reported in the literature. The behavior of Z^eff against the degree of ionization of the polymer and its concentration is also in good agreement with the theoretical expectations of the theory of ionic condensation. Osmotic measurements were also used in order to understand the influence of divalent cations (Mg²⁺, Ca²⁺, Ba²⁺) on Z^eff of the sodium salt of PAA at pH 9 and at different divalent/acrylate molar ratio. All the divalent cations depress Z^eff each of one at different degrees, confirming a specific divalent/polymer interaction. The energy of hydration of cations can explain most of the observed results with divalents.     

Integrative Cognitive Therapy for Depression: A Preliminary Investigation.

This study is a preliminary investigation of an integrative treatment aimed at improving the efficacy of cognitive therapy (CT) for depression. The development of the treatment protocol was based on process findings, which suggested that strategies used in CT to resolve alliance ruptures may actually exacerbate problems in the therapeutic relationship. The protocol integrates, within the traditional CT treatment manual, procedures to repair alliance ruptures that are derived from or consistent with humanistic and interpersonal therapies. Although conducted by inexperienced therapists, the integrative treatment led to greater improvement than a waiting-list condition. The results also compare favorably to previous findings for CT. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Contributing authors

Contributing authors     

Combined Ozone Pretreatment and Anaerobic Digestion for the Reduction of Biological Sludge Production in Wastewater Treatment

The ever-increasing amount of solid waste generated by wastewater treatment plants highlights emerging economic and environmental issues. In order to develop new processes producing less sludge, the use of ozone combined with anaerobic digestion was investigated for waste activated sludge treatment. This paper was aimed at evaluating the impact of ozone pretreatment on anaerobic digestion and particularly the enhancement of biogas production. Sludge solubilization was estimated in terms of modification of chemical oxygen demand, solids and nitrogen. Batch anaerobic digestion highlighted the enhancement of ozonated sludge biodegradability. Ozonation led to an increase in biogas production. The ozone dose of 0.15 g O₃/g total solids resulted in a considerable increase in the soluble COD ratio from 4% to 37%. This ozone dose achieved the highest increase in biogas production: 2.4 times greater than without chemical pretreatment.     

Note: a high transmission Faraday optical isolator in the 9.2 μm range

We have fabricated and characterized an n-doped InSb Faraday isolator in the mid-IR range (9.2 μm). A high isolation ratio (31(2) dB) and low insertion loss (1.9(3) dB) are obtained. Temperature dependance is analyzed. Further possible improvements are discussed, including the realization of a two-stage isolator. A similar design can be used to cover a wide wavelength range (λ ~ 7.5-30 μm).     

Free-form object reconstruction from silhouettes, occluding edges and texture edges: a unified and robust operator based on duality

In this paper, the duality in differential form is developed between a 3D primal surface and its dual manifold formed by the surface's tangent planes, i.e., each tangent plane of the primal surface is represented as a four-dimensional vector which constitutes a point on the dual manifold. The iterated dual theorem shows that each tangent plane of the dual manifold corresponds to a point on the original 3D surface, i.e., the dual of the dual goes back to the primal. This theorem can be directly used to reconstruct 3D surface from image edges by estimating the dual manifold from these edges. In this paper we further develop the work in our original conference papers resulting in the robust differential dual operator. We argue that the operator makes good use of the information available in the image data, by using both points of intensity discontinuity and their edge directions; we provide a simple physical interpretation of what the abstract algorithm is actually estimating and why it makes sense in terms of estimation accuracy; our algorithm operates on all edges in the images, including silhouette edges, self occlusion edges, and texture edges, without distinguishing their types (thus resulting in improved accuracy and handling locally concave surface estimation if texture edges are present); the algorithm automatically handles various degeneracies; and the algorithm incorporates new methodologies for implementing the required operations such as appropriately relating edges in pairs of images, evaluating and using the algorithm's sensitivity to noise to determine the accuracy of an estimated 3D point. Experiments with both synthetic and real images demonstrate that the operator is accurate, robust to degeneracies and noise, and general for reconstructing free-form objects from occluding edges and texture edges detected in calibrated images or video sequences.     

Rain or Snow Detection in Image Sequences Through Use of a Histogram of Orientation of Streaks

The detection of bad weather conditions is crucial for meteorological centers, specially with demand for air, sea and ground traffic management. In this article, a system based on computer vision is presented which detects the presence of rain or snow. To separate the foreground from the background in image sequences, a classical Gaussian Mixture Model is used. The foreground model serves to detect rain and snow, since these are dynamic weather phenomena. Selection rules based on photometry and size are proposed in order to select the potential rain streaks. Then a Histogram of Orientations of rain or snow Streaks (HOS), estimated with the method of geometric moments, is computed, which is assumed to follow a model of Gaussian-uniform mixture. The Gaussian distribution represents the orientation of the rain or the snow whereas the uniform distribution represents the orientation of the noise. An algorithm of expectation maximization is used to separate these two distributions. Following a goodness-of-fit test, the Gaussian distribution is temporally smoothed and its amplitude allows deciding the presence of rain or snow. When the presence of rain or of snow is detected, the HOS makes it possible to detect the pixels of rain or of snow in the foreground images, and to estimate the intensity of the precipitation of rain or of snow. The applications of the method are numerous and include the detection of critical weather conditions, the observation of weather, the reliability improvement of video-surveillance systems and rain rendering.     

Calibration of Cameras with Radially Symmetric Distortion

We present algorithms for plane-based calibration of general radially distorted cameras. By this, we understand cameras that have a distortion center and an optical axis such that the projection rays of pixels lying on a circle centered on the distortion center form a right viewing cone centered on the optical axis. The camera is said to have a single viewpoint (SVP) if all such viewing cones have the same apex (the optical center); otherwise, we speak of NSVP cases. This model encompasses the classical radial distortion model [5], fisheyes, and most central or noncentral catadioptric cameras. Calibration consists in the estimation of the distortion center, the opening angles of all viewing cones, and their optical centers. We present two approaches of computing a full calibration from dense correspondences of a single or multiple planes with known euclidean structure. The first one is based on a geometric constraint linking viewing cones and their intersections with the calibration plane (conic sections). The second approach is a homography-based method. Experiments using simulated and a broad variety of real cameras show great stability. Furthermore, we provide a comparison with Hartley-Kang's algorithm [12], which, however, cannot handle such a broad variety of camera configurations, showing similar performance.     

Partial 3D Shape Retrieval by Reeb Pattern Unfolding

This paper presents a novel approach for fast and efficient partial shape retrieval on a collection of 3D shapes. Each shape is represented by a Reeb graph associated with geometrical signatures. Partial similarity between two shapes is evaluated by computing a variant of their maximum common sub-graph.
By investigating Reeb graph theory, we take advantage of its intrinsic properties at two levels. First, we show that the segmentation of a shape by a Reeb graph provides charts with disk or annulus topology only. This topology control enables the computation of concise and efficient sub-part geometrical signatures based on parameterisation techniques. Secondly, we introduce the notion of Reeb pattern on a Reeb graph along with its structural signature. We show this information discards Reeb graph structural distortion and still depicts the topology of the related sub-parts. The number of combinations to evaluate in the matching process is then dramatically reduced by only considering the combinations of topology equivalent Reeb patterns.
The proposed framework is invariant against rigid transformations and robust against non-rigid transformations and surface noise. It queries the collection in interactive time (from 4 to 30 seconds for the largest queries). It outperforms the competing methods of the SHREC 2007 contest in term of NDCG vector and provides, respectively, a gain of 14.1% and 40.9% on the approaches by Biasotti et al. [ BMSF06 ] and Cornea et al. [ CDS*05 ].
As an application, we present an intelligent modelling-by-example system which enables a novice user to rapidly create new 3D shapes by composing shapes of a collection having similar sub-parts.