Video Object Tracking And Analysis For Computer Assisted Surgery

Pedicle screw insertion technique has made revolution in the surgical treatment of spinal fractures and spinal disorders. Although X- ray fluoroscopy based navigation is popular, there is risk of prolonged exposure to X- ray radiation. Systems that have lower radiation risk are generally quite expensive. The position and orientation of the drill is clinically very important in pedicle screw fixation. In this paper, the position and orientation of the marker on the drill is determined using pattern recognition based methods, using geometric features, obtained from the input video sequence taken from CCD camera. A search is then performed on the video frames after preprocessing, to obtain the exact position and orientation of the drill. An animated graphics, showing the instantaneous position and orientation of the drill is then overlaid on the processed video for real time drill control and navigation

Probabilistic sonar scan matching for an AUV

This paper proposes MSISpIC, a probabilistic sonar scan matching algorithm for the localization of an autonomous underwater vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), the robot displacement estimated through dead-reckoning using a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method is an extension of the pIC algorithm. An extended Kalman filter (EKF) is used to estimate the robot-path during the scan in order to reference all the range and bearing measurements as well as their uncertainty to a scan fixed frame before registering. The major contribution consists of experimentally proving that probabilistic sonar scan matching techniques have the potential to improve the DVL-based navigation. The algorithm has been tested on an AUV guided along a 600 m path within an abandoned marina underwater environment with satisfactory results

Lógica en la toma de decisiones de inversión en el sector de extracción de petróleo y gas natural

Este documento se centra en la presentación de información y análisis de la misma a la hora de establecer la manera en que empresas del sector de extracción de gas natural y generación de energía a base de dicho recurso, toman decisiones en cuanto a inversión, centrándose en la lógica que usan a la hora de emprender este proceso. Esto debido a la constante necesidad de establecer procesos que permitan tomar decisiones más acertadas, incluyendo todas las herramientas posibles para tal fin. La lógica es una de estas herramientas, pues permite encadenar factores con el fin de obtener resultados positivos. Por tal razón, se hace importante conocer el uso de esta herramienta, teniendo en cuentas de qué manera y en que contextos es usada. Con el fin de tener una mayor orientación, este estudio estará centrado en un sector específico, el cual es el de la extracción de petróleo y gas natural. Lo anterior entendiendo la necesidad existente de fundamentación teórica que permita establecer de manera clara la forma apropiada de tomar decisiones en un sector tan diverso y complejo como lo es el mencionado. El contexto empresarial actual exige una visión global, no basada en la lógica lineal causal que hoy se tiene como referencia. El sector de extracción de petróleo y gas natural es un ejemplo particular en cuanto a la manera en cuanto se toman decisiones en inversión, puesto que en su mayoría son empresas de capital intensivo, las cuales mantienen un flujo elevado de recursos monetarios.

VLSI architecture for motion estimation in underwater imaging

El treball desenvolupat en aquesta tesi aprofundeix i aporta solucions innovadores en el camp orientat a tractar el problema de la correspondència en imatges subaquàtiques. En aquests entorns, el que realment complica les tasques de processat és la falta de contorns ben definits per culpa d'imatges esborronades; un fet aquest que es deu fonamentalment a il·luminació deficient o a la manca d'uniformitat dels sistemes d'il·luminació artificials. Els objectius aconseguits en aquesta tesi es poden remarcar en dues grans direccions. Per millorar l'algorisme d'estimació de moviment es va proposar un nou mètode que introdueix paràmetres de textura per rebutjar falses correspondències entre parells d'imatges. Un seguit d'assaigs efectuats en imatges submarines reals han estat portats a terme per seleccionar les estratègies més adients. Amb la finalitat d'aconseguir resultats en temps real, es proposa una innovadora arquitectura VLSI per la implementació d'algunes parts de l'algorisme d'estimació de moviment amb alt cost computacional.

As atitudes dos professores face à inclusão de alunos com deficiência : o contacto com a deficiência

RESUMO: Actualmente as práticas de exclusão evoluíram para uma perspectiva de inclusão, assim como para a consciencialização dos direitos e deveres de cada um, como forma de dar resposta à sociedade heterogénea existente. A visão baseada nos sistemas de identificação e classificação dos sujeitos em várias categorias de deficiências era algo muito usual, mas que foi abolida, dando assim lugar ao conceito de Necessidades Educativas Especiais, com uma óptica mais abrangente, tendo em conta o contexto em que o sujeito está envolvido (Nunes, 2000). As atitudes dos professores face aos alunos com deficiência têm melhorado significativamente (Ribeiro, 1999), no entanto o processo de inclusão destas crianças no ensino regular não está isento de problemas. Neste sentido, e para que este desafio seja ultrapassado com sucesso, torna-se essencial que os professores modifiquem as suas atitudes e passem a desempenhar um papel mais activo nas suas funções, devendo para isso, começar por adaptar o currículo, e posteriormente repensar as suas estratégias e métodos de trabalho, como forma a responder às necessidades de todos os alunos (Ainscow, 1997). O objectivo principal deste estudo é verificar se o contacto com a deficiência (a nível da experiência no ensino, formação inicial e contacto na infância/juventude), por parte dos professores, influencia as suas atitudes em relação à formação necessária para a inclusão de alunos com deficiência, bem como às vantagens que esta representa para esses mesmos alunos. A amostra foi constituída por 672 professores do ensino regular, todos estão actualmente no activo e leccionam níveis de ensino do Pré-Escolar ao Ensino Secundário, de Norte a Sul do país. (N = 482 do género feminino e N =190 do género masculino). O instrumento de avaliação aplicado foi o questionário APIAD – Atitude dos Professores face à Inclusão de Alunos com Deficiência (Leitão, 2011). Concluiu-se que a experiência no ensino de alunos com deficiência influencia significativamente a atitude dos professores face à formação necessária (deficiência motora: p<0,001; deficiência auditiva: p<0,001; deficiência visual: p<0,001; deficiência mental: p=0,004) e face às vantagens da inclusão para os alunos com deficiência (deficiência motora: p=0,005; deficiência auditiva: p<0,001; deficiência visual: p<0,001; deficiência mental: p=0,022). No que se refere ao contacto com pessoas com deficiência durante a formação inicial, concluiu-se que existem diferenças significativas na atitude dos professores face às vantagens da inclusão para os alunos com deficiência (deficiência motora: p<0,001; deficiência auditiva: p<0,001; deficiência visual: p<0,001; deficiência mental: p<0,001). No entanto, no que respeita à formação, a atitude dos professores não difere, independentemente de terem tido esse contacto (deficiência motora: p=0,393; deficiência auditiva: p=0,456; deficiência visual: p=0,055; deficiência mental: p=0,342). Relativamente ao contacto com pessoas com deficiência durante a infância/juventude conclui-se que não existem diferenças na atitude dos professores em relação à formação necessária (deficiência motora: p=0,893; deficiência auditiva: p=0,667; deficiência visual: p=0,459; deficiência mental: p=0,918). Por sua vez, no que respeita às vantagens da inclusão para os alunos com deficiência, esta variável só influencia significativamente a atitude dos professores no caso da deficiência visual (deficiência motora: p=0,154; deficiência auditiva: p=0,100; deficiência visual: p=0,045; deficiência mental: p=0,149). ABSTRACT: Currently the exclusionary practices evolved to an inclusion perspective, as well as the awareness of rights and duties of each one as a way to reply to the existing heterogeneous society. The vision-based systems for identification and classification of subjects into various categories of disabilities was very unusual, but it was abolished, giving way to the concept of Special Educational Needs, with a broader perspective, considering the context in which the subject is involved (Nunes, 2000). The teachers attitude face to the students with disabilities have improved significantly (Ribeiro, 1999), however the process of inclusion of these children in regular education isn't exempt of problems. In this direction and so this challenge is exceeded successfully, it is essential that teachers change their attitudes and start to perform a more active role in their functions, and to do so, start by adapting the curriculum and then rethink their strategies and working methods, in order to meet the needs of all students (Ainscow, 1997). The main purpose of this study is to verify that the contact with the disability (educational level of experience, initial formation and contact in childhood/youth), among teachers, influences their attitudes towards the needed formation for the inclusion of students with disabilities as well as the benefits that this represents for them. The sample consisted by 672 regular educational teachers, all currently in employment and teaching from Preschool to High school, from North to South. (N = 482 females and N = 190 males). The evaluation instrument used was the survey APIAD - Teachers attitude towards the inclusion of students with disabilities (Leitão, 2011). It was concluded that the experience in teaching students with disabilities influences significantly the teachers attitude faced to the necessary formation (motor disability: p<0,001; hearing impairment: p<0,001; visual impairment: p<0,001; mental disability: p=0,004) and faced to the inclusion benefits for students with disabilities (motor disability: p=0,005; hearing impairment: p<0,001; visual impairment: p<0,001; mental disability: p=0,022).Concerning to the contact with people with disabilities during the initial formation, it was concluded that there are significant differences in the teachers attitude face to the inclusion benefits for students with disabilities (motor disability: p<0,001; hearing impairment: p<0,001; visual impairment: p<0,001; mental disability: p<0,001). In relation to the formation, the teachers attitude is the same, regardless of whether or not they have had such contact (motor disability: p=0,393; hearing impairment: p=0,456; visual impairment: p=0,055; mental disability: p=0,342). Regarding to the contact with people with disabilities during childhood/youth, it was concluded that there is no difference in the teachers attitude in relation to the formation needed (motor disability: p=0,893; hearing impairment: p=0,667; visual impairment: p=0,459; mental disability: p=0,918). On the other way, regarding to the inclusion benefits for students with disabilities, this influences significantly the teachers attitude just in the visual impairment. (motor disability: p=0,154; hearing impairment: p=0,100; visual impairment: p=0,045; mental disability: p=0,149).

Final report on research project PS2010, proof of concept of automated mapping of weeds in arable fields

Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).

‘Low carbon’ scenarios, roadmaps, transitions and pathways: an overview and discussion

There are a range of studies based in the low carbon arena which use various ‘futures’- based techniques as ways of exploring uncertainties. These techniques range from ‘scenarios’ and ‘roadmaps’ through to ‘transitions’ and ‘pathways’ as well as ‘vision’-based techniques. The overall aim of the paper is therefore to compare and contrast these techniques to develop a simple working typology with the further objective of identifying the implications of this analysis for RETROFIT 2050. Using recent examples of city-based and energy-based studies throughout, the paper compares and contrasts these techniques and finds that the distinctions between them have often been blurred in the field of low carbon. Visions, for example, have been used in both transition theory and futures/Foresight methods, and scenarios have also been used in transition-based studies as well as futures/Foresight studies. Moreover, Foresight techniques which capture expert knowledge and map existing knowledge to develop a set of scenarios and roadmaps which can inform the development of transitions and pathways can not only help potentially overcome any ‘disconnections’ that may exist between the social and the technical lenses in which such future trajectories are mapped, but also promote a strong ‘co-evolutionary’ content.

Real time video segmentation for recognising paint marks on bad wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are based on visual analysis. Machine vision based approach has been done to emulate the visual abilities of human operator to enable automation of the process. Through this process bad sleepers are identified, and a spot is marked on it with specific color (blue in the current case) on the rail so that the maintenance operators are able to identify the spot and replace the sleeper. The motive of this thesis is to help the operators to identify those sleepers which are marked by color (spots), using an “Intelligent Vehicle” which is capable of running on the track. Capturing video while running on the track and segmenting the object of interest (spot) through this vehicle; we can automate this work and minimize the human intuitions. The video acquisition process depends on camera position and source light to obtain fine brightness in acquisition, we have tested 4 different types of combinations (camera position and source light) here to record the video and test the validity of proposed method. A sequence of real time rail frames are extracted from these videos and further processing (depending upon the data acquisition process) is done to identify the spots. After identification of spot each frame is divided in to 9 regions to know the particular region where the spot lies to avoid overlapping with noise, and so on. The proposed method will generate the information regarding in which region the spot lies, based on nine regions in each frame. From the generated results we have made some classification regarding data collection techniques, efficiency, time and speed. In this report, extensive experiments using image sequences from particular camera are reported and the experiments were done using intelligent vehicle as well as test vehicle and the results shows that we have achieved 95% success in identifying the spots when we use video as it is, in other method were we can skip some frames in pre-processing to increase the speed of video but the segmentation results we reduced to 85% and the time was very less compared to previous one. This shows the validity of proposed method in identification of spots lying on wooden railway sleepers where we can compromise between time and efficiency to get the desired result.

Motion cue analysis for parkinsonian gait recognition

This paper presents a computer-vision based marker-free method for gait-impairment detection in Patients with Parkinson's disease (PWP). The system is based upon the idea that a normal human body attains equilibrium during the gait by aligning the body posture with Axis-of-Gravity (AOG) using feet as the base of support. In contrast, PWP appear to be falling forward as they are less-able to align their body with AOG due to rigid muscular tone. A normal gait exhibits periodic stride-cycles with stride-angle around 45o between the legs, whereas PWP walk with shortened stride-angle with high variability between the stride-cycles. In order to analyze Parkinsonian-gait (PG), subjects were videotaped with several gait-cycles. The subject's body was segmented using a color-segmentation method to form a silhouette. The silhouette was skeletonized for motion cues extraction. The motion cues analyzed were stride-cycles (based on the cyclic leg motion of skeleton) and posture lean (based on the angle between leaned torso of skeleton and AOG). Cosine similarity between an imaginary perfect gait pattern and the subject gait patterns produced 100% recognition rate of PG for 4 normal-controls and 3 PWP. Results suggested that the method is a promising tool to be used for PG assessment in home-environment.

Acelerando algoritmos de baixo nível em visão robótica com hardware reconfigurável

A challenge that remains in the robotics field is how to make a robot to react in real time to visual stimulus. Traditional computer vision algorithms used to overcome this problem are still very expensive taking too long when using common computer processors. Very simple algorithms like image filtering or even mathematical morphology operations may take too long. Researchers have implemented image processing algorithms in high parallelism hardware devices in order to cut down the time spent in the algorithms processing, with good results. By using hardware implemented image processing techniques and a platform oriented system that uses the Nios II Processor we propose an approach that uses the hardware processing and event based programming to simplify the vision based systems while at the same time accelerating some parts of the used algorithms

Para uma gramática da produção: análise da marca mesmo sob o enfoque da teoria das operações predicativas e enunciativas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A-TIRMA: A small autonomous sailboat

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

An analysis of automatic gender classification

[EN]Different researches suggest that inner facial features are not the only discriminative features for tasks such as person identification or gender classification. Indeed, they have shown an influence of features which are part of the local face context, such as hair, on these tasks. However, object-centered approaches which ignore local context dominate the research in computational vision based facial analysis. In this paper, we performed an analysis to study which areas and which resolutions are diagnostic for the gender classification problem. We first demonstrate the importance of contextual features in human observers for gender classification using a psychophysical ”bubbles” technique.

Reconstruction from image correspondences

A single picture provides a largely incomplete representation of the scene one is looking at. Usually it reproduces only a limited spatial portion of the scene according to the standpoint and the viewing angle, besides it contains only instantaneous information. Thus very little can be understood on the geometrical structure of the scene, the position and orientation of the observer with respect to it remaining also hard to guess. When multiple views, taken from different positions in space and time, observe the same scene, then a much deeper knowledge is potentially achievable. Understanding inter-views relations enables construction of a collective representation by fusing the information contained in every single image. Visual reconstruction methods confront with the formidable, and still unanswered, challenge of delivering a comprehensive representation of structure, motion and appearance of a scene from visual information. Multi-view visual reconstruction deals with the inference of relations among multiple views and the exploitation of revealed connections to attain the best possible representation. This thesis investigates novel methods and applications in the field of visual reconstruction from multiple views. Three main threads of research have been pursued: dense geometric reconstruction, camera pose reconstruction, sparse geometric reconstruction of deformable surfaces. Dense geometric reconstruction aims at delivering the appearance of a scene at every single point. The construction of a large panoramic image from a set of traditional pictures has been extensively studied in the context of image mosaicing techniques. An original algorithm for sequential registration suitable for real-time applications has been conceived. The integration of the algorithm into a visual surveillance system has lead to robust and efficient motion detection with Pan-Tilt-Zoom cameras. Moreover, an evaluation methodology for quantitatively assessing and comparing image mosaicing algorithms has been devised and made available to the community. Camera pose reconstruction deals with the recovery of the camera trajectory across an image sequence. A novel mosaic-based pose reconstruction algorithm has been conceived that exploit image-mosaics and traditional pose estimation algorithms to deliver more accurate estimates. An innovative markerless vision-based human-machine interface has also been proposed, so as to allow a user to interact with a gaming applications by moving a hand held consumer grade camera in unstructured environments. Finally, sparse geometric reconstruction refers to the computation of the coarse geometry of an object at few preset points. In this thesis, an innovative shape reconstruction algorithm for deformable objects has been designed. A cooperation with the Solar Impulse project allowed to deploy the algorithm in a very challenging real-world scenario, i.e. the accurate measurements of airplane wings deformations.