Unsupervised learning of categorical segments in image collections

Which one comes first: segmentation or recognition? We propose a probabilistic framework for carrying out the two simultaneously. The framework combines an LDA ‘bag of visual words’ model for recognition, and a hybrid parametric-nonparametric model for segmentation. If applied to a collection of images, our framework can simultaneously discover the segments of each image, and the correspondence between such segments. Such segments may be thought of as the ‘parts’ of corresponding objects that appear in the image collection. Thus, the model may be used for learning new categories, detecting/classifying objects, and segmenting images

Non-Parametric Probabilistic Image Segmentation

We propose a simple probabilistic generative model for image segmentation. Like other probabilistic algorithms (such as EM on a Mixture of Gaussians) the proposed model is principled, provides both hard and probabilistic cluster assignments, as well as the ability to naturally incorporate prior knowledge. While previous probabilistic approaches are restricted to parametric models of clusters (e.g., Gaussians) we eliminate this limitation. The suggested approach does not make heavy assumptions on the shape of the clusters and can thus handle complex structures. Our experiments show that the suggested approach outperforms previous work on a variety of image segmentation tasks

Authority-Sharing Control of Assistive Robotic Walkers

A recognized consequence of population aging is a reduced level of mobility, which undermines the life quality of several senior citizens. A promising solution is represented by assisitive robotic walkers, combining the benefits of standard walkers (improved stability and physical support) with sensing and computing ability to guarantee cognitive support. In this context, classical robot control strategies designed for fully autonomous systems (such as fully autonomous vehicles, where the user is excluded from the loop) are clearly not suitable, since the user’s residual abilities must be exploited and practiced. Conversely, to guarantee safety even in the presence of user’s cognitive deficits, the responsibility of controlling the vehicle motion cannot be entirely left to the assisted person. The authority-sharing paradigm, where the control authority, i.e., the capability of controlling the vehicle motion, is shared between the human user and the control system, is a promising solution to this problem. This research develops control strategies for assistive robotic walkers based on authority-sharing: this way, we ensure that the walker provides the user only the help he/she needs for safe navigation. For instance, if the user requires just physical support to reach the restrooms, the robot acts as a standard rollator; however, if the user’s cognitive abilities are limited (e.g., the user does not remember where the restrooms are, or he/she does not recognize obstacles on the path), the robot also drives the user towards the proper corridors, by planning and following a safe path to the restrooms. The authority is allocated on the basis of an error metric, quantifying the distance between the current vehicle heading and the desired movement direction to perform the task. If the user is safely performing the task, he/she is endowed with control authority, so that his/her residual abilities are exploited. Conversely, if the user is not capable of safely solving the task (for instance, he/is going to collide with an obstacle), the robot intervenes by partially or totally taking the control authority to help the user and ensure his/her safety (for instance, avoiding the collision). We provide detailed control design and theoretical and simulative analyses of the proposed strategies. Moreover, extensive experimental validation shows that authority-sharing is a successful approach to guide a senior citizen, providing both comfort and safety. The most promising solutions include the use of haptic systems to suggest the user a proper behavior, and the modification of the perceived physical interaction of the user with the robot to gradually share the control authority using a variable stiffness vehicle handling

Surface plasmon resonance based on molecularly imprinted nanoparticles for the picomolar detection of the iron regulating hormone Hepcidin-25

Molecular modelling

Unsupervised Learning of Categorical Segments in Image Collections

Which one comes first: segmentation or recognition? We propose a unified framework for carrying out the two simultaneously and without supervision. The framework combines a flexible probabilistic model for representing the shape and appearance of each segment, with the popular "bag of visual words" model for recognition. If applied to a collection of images, our framework can simultaneously discover the segments of each image, and the correspondence between such segments, without supervision. Such recurring segments may be thought of as the "parts" of corresponding objects that appear multiple times in the image collection. Thus, the model may be used for learning new categories, detecting/classifying objects, and segmenting images, without using expensive human annotation

Dos cuentos de Ambrosetti

No solamente en el trazado de la historia de las investigaciones paleontológicas argentinas deben merecer lugar distinguido, espectable, el nombre y la fecunda producción de Juan Bautista Ambrosetti (1865-1917), el entrerriano alumno de don Florentino Ameghino. También lo reclaman para sí las letras del país; aunque esa su afición —a veces queremos creer que constituye un pasatiempo al cabo de su intensa faena científica— resulta todavía para muchos críticos una faceta poco menos que desconocida.Universidad Nacional de La Plat

Dos cuentos de Ambrosetti

No solamente en el trazado de la historia de las investigaciones paleontológicas argentinas deben merecer lugar distinguido, espectable, el nombre y la fecunda producción de Juan Bautista Ambrosetti (1865-1917), el entrerriano alumno de don Florentino Ameghino. También lo reclaman para sí las letras del país; aunque esa su afición —a veces queremos creer que constituye un pasatiempo al cabo de su intensa faena científica— resulta todavía para muchos críticos una faceta poco menos que desconocida.Universidad Nacional de La Plat

Carving from Ray-Tracing Constraints: IRT-Carving

We present a new algorithm for improving an available (conservative) estimate of the shape of an object using constraints from ray-tracing. In particular, we exploit incoherences between the lit portions of the object - detected on a set of acquired images - and the shadows that the current estimate casts on itself. Whenever a contradiction is found the current estimate is modified in order to remove the inconsistency. Sufficient conditions for the correctness of the algorithm and a discussion of their validity are provided. Finally, we describe a simple implementation of the method and present some preliminary experimental results from computer simulations

Potential Fossilized Sulfide-Oxidizing Bacteria in the Upper Miocene Sulfur-Bearing Limestones From the Lorca Basin (SE Spain): Paleoenvironmental Implications

The sulfur-bearing limestones interbedded in the upper Miocene diatomaceous sediments (Tripoli Formation) of the Lorca Basin (SE Spain) are typified, as other Mediterranean coeval carbonate and gypsum deposits, by filamentous, circular and rod-shaped microstructures of controversial origin. These features have been interpreted both as fecal pellets of brine shrimps and/or of copepods, remains of algae or cyanobacteria and fossilized sulfide-oxidizing bacteria. To shed light on their origin, a multidisciplinary study including optical, UV and scanning electron microscopy, Raman microspectroscopy, and geochemical (carbon and oxygen stable isotopes) analyses has been carried out on three carbonate beds exposed along the La Serrata ridge. The different composition of the filamentous and circular objects with respect to the rod-shaped microstructures suggest that the former represent remains of bacteria, while the latter fecal pellets of deposit- or suspension-feeder organisms. Size and shape of the filamentous and circular microfossils are consistent with their assignment to colorless sulfide-oxidizing bacteria like Beggiatoa (or Thioploca) and Thiomargarita, which is further supported by the presence, only within the microfossil body, of tiny pyrite grains. These grains possibly result from early diagenetic transformation of original sulfur globules stored by the bacteria, which are a diagnostic feature of this group of prokaryotes. The development of microbial communities dominated by putative sulfide-oxidizing bacteria at Lorca was favored by hydrogen sulfide flows generated through degradation of organic matter by sulfate-reducing bacteria thriving in underlying organic-rich sediments