Robot Motion Vision by Fixation

In many motion-vision scenarios, a camera (mounted on a moving vehicle) takes images of an environment to find the "motion'' and shape. We introduce a direct-method called fixation for solving this motion-vision problem in its general case. Fixation uses neither feature-correspondence nor optical-flow. Instead, spatio-temporal brightness gradients are used directly. In contrast to previous direct methods, fixation does not restrict the motion or the environment. Moreover, fixation method neither requires tracked images as its input nor uses mechanical tracking for obtaining fixated images. The experimental results on real images are presented and the implementation issues and techniques are discussed.

Representing team behaviours from noisy data using player role

Due to their unobtrusive nature, vision-based approaches to tracking sports players have been preferred over wearable sensors as they do not require the players to be instrumented for each match. Unfortunately however, due to the heavy occlusion between players, variation in resolution and pose, in addition to fluctuating illumination conditions, tracking players continuously is still an unsolved vision problem. For tasks like clustering and retrieval, having noisy data (i.e. missing and false player detections) is problematic as it generates discontinuities in the input data stream. One method of circumventing this issue is to use an occupancy map, where the field is discretised into a series of zones and a count of player detections in each zone is obtained. A series of frames can then be concatenated to represent a set-play or example of team behaviour. A problem with this approach though is that the compressibility is low (i.e. the variability in the feature space is incredibly high). In this paper, we propose the use of a bilinear spatiotemporal basis model using a role representation to clean-up the noisy detections which operates in a low-dimensional space. To evaluate our approach, we used a fully instrumented field-hockey pitch with 8 fixed high-definition (HD) cameras and evaluated our approach on approximately 200,000 frames of data from a state-of-the-art real-time player detector and compare it to manually labeled data.

The hybrid stranger and intercultural hermeneutics

The category of the stranger has experienced a renaissance in contemporary social theory. Within this burgeoning literature, a new conceptualisation has emerged known as the 'in-between stranger' or the 'hybrid of modernity'. The formulation of this stranger has raised epistemological concerns. Not only can the hybrid expose the misunderstanding between Self and Other or between two life-worlds, it is able to transcend the self/other dichotomy. The unresolved hermeneutic problem -the meeting with strangers -results in uncertainty, in particular uncertainty about how to read and respond to unfamiliar social situations. What is interesting is not the fact that misunderstanding occurs between the host and the stranger, but that the stranger's physical nearness and social distance fosters an interpretative view of the world that is not accessible to either the host (Self) or parent group (Other). The position of hybrid strangers purportedly encourages a critical and 'objective' stance that transcends conventional and 'situated' knowledge. The discourse on 'the stranger', beginning with Simmel, has constructed the hybrid stranger as disinterested third party. This in-between, third position allows hybrid strangers to see things more clearly and/or differently than those occupying opposing positions or cultural perspectives. In this paper I critically examine the nature of this third type of consciousness and its association with the idea of the intercultural.

Measuring depth accuracy in RGBD cameras

This paper presents the comparison between the Microsoft Kinect depth sensor and the Asus Xtion for computer vision applications. Depth sensors, known as RGBD cameras,
project an infrared pattern and calculate the depth from the reflected light using an infrared sensitive camera. In this research, we compare the depth sensing capabilities of the two sensors under various conditions. The purpose is to give the reader a background to whether use the Microsoft Kinect or Asus Xtion sensor to solve a specific computer vision problem. The properties of the two depth sensors were investigated by conducting a series of experiments evaluating the accuracy of the sensors under various conditions, which shows the advantages and disadvantages of both Microsoft Kinect and Asus Xtion sensor.

Detecção de metamidofós em solos por métodos ecotoxicológico e cromatografia líquida acoplada à espectrometria de massas sequencial (LC-MS/MS)

Soil contamination by pesticides is an environmental problem that needs to be monitored and avoided. However, the lack of fast, accurate and low cost analytical methods for discovering residual pesticide in complex matrices, such as soil, is a problem still unresolved. This problem needs to be solved before we are able to assess the quality of environmental samples. The intensive use of pesticides has increased since the 60s, because the dependence of their use, causing biological imbalances and promoting resistance and recurrence of high populations of pests and pathogens (upwelling). This has contributed to the appearance of new pests that were previously under natural control. To develop analytical methods that are able to quantify residues pesticide in complex environment. It is still a challenge for many laboratories. The integration of two analytical methods one ecotoxicological and another chemical demonstrates the potential for environmental analysis of methamidophos. The aim of this study was to evaluate an ecotoxicological method as "screening" analytical methamidophos in the soil and perform analytical confirmation in the samples of the concentration of the analyte by chemical method LC-MS/MS In this work we tested two soils: a clayey and sandy, both in contact with the kinetic methamidophos model followed pseudo-second order. The clay soil showed higher absorption of methamidophos and followed the Freundlich model, while the sandy, the Langmuir model. The chemical method was validated LC-MS/MS satisfactory, showing all parameters of linearity, range, precision, accuracy, and sensitivity adequate. In chronic ecotoxicological tests with C. dubia, the NOEC was 4.93 and 3.24 for ng L-1 of methamidophos to elutriate assays of sandy and clay soils, respectively. The method for ecotoxicological levels was more sensitive than LC-MS/MS detection of methamidophos, loamy and sandy soils. However, decreasing the concentration of the standard for analytical methamidophos and adjusting for the validation conditions chemical acquires a limit of quantification (LOQ) in ng L-1, consistent with the provisions of ecotoxicological test. The methods described should be used as an analytical tool for methamidophos in soil, and the ecotoxicological analysis can be used as a "screening" and LC-MS/MS as confirmatory analysis of the analyte molecule, confirming the objectives of this work

Modeling and measuring the spatial relation "along": Regions, contours and fuzzy sets

The analysis of spatial relations among objects in an image is an important vision problem that involves both shape analysis and structural pattern recognition. In this paper, we propose a new approach to characterize the spatial relation along, an important feature of spatial configurations in space that has been overlooked in the literature up to now. We propose a mathematical definition of the degree to which an object A is along an object B, based on the region between A and B and a degree of elongatedness of this region. In order to better fit the perceptual meaning of the relation, distance information is included as well. In order to cover a more wide range of potential applications, both the crisp and fuzzy cases are considered. In the crisp case, the objects are represented in terms of 2D regions or ID contours, and the definition of the alongness between them is derived from a visibility notion and from the region between the objects. However, the computational complexity of this approach leads us to the proposition of a new model to calculate the between region using the convex hull of the contours. On the fuzzy side, the region-based approach is extended. Experimental results obtained using synthetic shapes and brain structures in medical imaging corroborate the proposed model and the derived measures of alongness, thus showing that they agree with the common sense. (C) 2011 Elsevier Ltd. All rights reserved.

A Solution of the Figure-ground Problem for Biological Vision

A neural network model of 3-D visual perception and figure-ground separation by visual cortex is introduced. The theory provides a unified explanation of how a 2-D image may generate a 3-D percept; how figures pop-out from cluttered backgrounds; how spatially sparse disparity cues can generate continuous surface representations at different perceived depths; how representations of occluded regions can be completed and recognized without usually being seen; how occluded regions can sometimes be seen during percepts of transparency; how high spatial frequency parts of an image may appear closer than low spatial frequency parts; how sharp targets are detected better against a figure and blurred targets are detector better against a background; how low spatial frequency parts of an image may be fused while high spatial frequency parts are rivalrous; how sparse blue cones can generate vivid blue surface percepts; how 3-D neon color spreading, visual phantoms, and tissue contrast percepts are generated; how conjunctions of color-and-depth may rapidly pop-out during visual search. These explanations arise derived from an ecological analysis of how monocularly viewed parts of an image inherit the appropriate depth from contiguous binocularly viewed parts, as during DaVinci stereopsis. The model predicts the functional role and ordering of multiple interactions within and between the two parvocellular processing streams that join LGN to prestriate area V4. Interactions from cells representing larger scales and disparities to cells representing smaller scales and disparities are of particular importance.

A robust set-valued state estimation approach to the problem of vision based SLAM for mobile robots

The problem of visual simultaneous localization and mapping (SLAM) is examined in this paper using ideas and algorithms from robust control and estimation theory. Using a stereo-vision based sensor, a nonlinear measurement model is derived which leads to nonlinear measurements of the landmark coordinates along with optical flow based measurements of the relative robot-landmark velocity. Using a novel analytical measurement transformation, the nonlinear SLAM problem is converted into the linear filter is guaranteed stable and the ALAM state estimation error is bounded within an ellipsoidal set. No similar results are available for the commonly employed extended Kalman filter which is known to exhibit divergent and inconsistency characteristics in practice.

A robust solution to the stereo-vision-based simultaneous localization and mapping problem with steady and moving landmarks

The problem of visual simultaneous localization and mapping (SLAM) is examined in this paper using recently developed ideas and algorithms from modern robust control and estimation theory. A nonlinear model for a stereo-vision-based sensor is derived that leads to nonlinear measurements of the landmark coordinates along with optical flow-based measurements of the relative robot-landmark velocity. Using a novel analytical measurement transformation, the nonlinear SLAM problem is converted into the linear domain and solved using a robust linear filter. Actually, the linear filter is guaranteed stable and the SLAM state estimation error is bounded within an ellipsoidal set. A mathematically rigorous stability proof is given that holds true even when the landmarks move in accordance with an unknown control input. No similar results are available for the commonly employed extended Kalman filter, which is known to exhibit divergence and inconsistency characteristics in practice. A number of illustrative examples are given using both simulated and real vision data that further validate the proposed method.

Binocular vision in insects: How mantids solve the correspondence problem

Praying mantids use binocular cues to judge whether their prey is in striking distance. When there are several moving targets within their binocular visual field, mantids need to solve the correspondence problem. They must select between the possible pairings of retinal images in the two eyes so that they can strike at a single real target. In this study, mantids were presented with two targets in various configurations, and the resulting fixating saccades that precede the strike were analyzed. The distributions of saccades show that mantids consistently prefer one out of several possible matches. Selection is in part guided by the position and the spatiotemporal features of the target image in each eye. Selection also depends upon the binocular disparity of the images, suggesting that insects can perform local binocular computations. The pairing rules ensure that mantids tend to aim at real targets and not at “ghost” targets arising from false matches.

Hearing and vision:the age old problem

Opticians and audiologists tend to see the same people. Many factors that are associated with poorer vision, whether hereditary, pre-natal, or post-natal, are also associated with poorer hearing. The most common factor is simply old age. According to the Royal National Institute for Deaf People (RNID), more than half of all people aged over 60 have some degree of hearing loss and are gradually losing their hearing as part of the ageing process – a process known as presbycusis.

Where Are We After Five Editions?: Robot Vision Challenge, a Competition that Evaluates Solutions for the Visual Place Classification Problem

This article describes the Robot Vision challenge, a competition that evaluates solutions for the visual place classification problem. Since its origin, this challenge has been proposed as a common benchmark where worldwide proposals are measured using a common overall score. Each new edition of the competition introduced novelties, both for the type of input data and subobjectives of the challenge. All the techniques used by the participants have been gathered up and published to make it accessible for future developments. The legacy of the Robot Vision challenge includes data sets, benchmarking techniques, and a wide experience in the place classification research that is reflected in this article.

Rehabilitation staff perspectives on training for problem-solving therapy for primary care in a low vision service

Vision rehabilitation staff were trained to deliver problem-solving therapy for primary care (PSTPC) over the telephone to adults with depressive symptoms and low vision. Training was a 2-day workshop, completion of training cases, and assessment of treatment fidelity. Staff perspectives of training and challenges in PST-PC delivery were explored. Telephone-administered semistructured interviews were conducted pre- and post-workshop and following PST-PC competency. In all, 14 staff (mean age = 47.64 years, SD = 12.68 years, 93% females) achieved competency and 6 withdrew. Results showed an increased understanding of PST-PC from pre- to post-workshop (Z = −2.71, p = .007) and pre-workshop to post-competency (Z = −3.09, p = .002). A high level of satisfaction with training was reported. Staff challenges included the clients’ ability to define problems and brainstorm solutions. Training enabled staff to competently deliver PST-PC and may serve as a model for integrating depression care into vision rehabilitation services recommended by international guidelines.