983 resultados para Robot Vision


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How can we reach out to institutions, artists and audiences with sometimes radically different agendas to encourage them to see, participate in and support the development of new practices and programs in the performing arts? In this paper, based on a plenary panel at PSi#18 Performance Culture Industry at the University of Leeds, Clarissa Ruiz (Columbia), AnuradhaKapur (India) and Sheena Wrigley (England) together with interloctorBree Hadley (Australia) speak about their work in as policy-makers, managers and producers in the performing arts in Europe, Asia and America over the past several decades. Acknowledged trailblazers in their fields, Ruiz, Kapur and Wrigley all have a commitment to creating a vital, viable and sustainable performing arts ecologies. Each has extensive experience in performance, politics, and the challenging process of managing histories, visions, stakeholders, and sometimes scarce resources to generate lasting benefits for the various communities have worked for, with and within. Their work, cultivating new initiatives, programs or policy has made them expert at brokering relationships in and in between private, public and political spheres to elevate the status of and support for performing arts as a socially and economically beneficial activity everyone can participate in. Each gives examples from their own practice to provide insight into how to negotiate the interests of artistic, government, corporate, community and education partners, and the interests of audiences, to create aesthetic, cultural and / or economic value. Together, their views offer a compelling set of perspectives on the changing meanings of the ‘value of the arts’ and the effects this has had for the artists that make and arts organisations that produce and present work in a range of different regional, national and cross-national contexts.

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In this paper, we present a monocular vision based autonomous navigation system for Micro Aerial Vehicles (MAVs) in GPS-denied environments. The major drawback of monocular systems is that the depth scale of the scene can not be determined without prior knowledge or other sensors. To address this problem, we minimize a cost function consisting of a drift-free altitude measurement and up-to-scale position estimate obtained using the visual sensor. We evaluate the scale estimator, state estimator and controller performance by comparing with ground truth data acquired using a motion capture system. All resources including source code, tutorial documentation and system models are available online.

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Evolutionary computation is an effective tool for solving optimization problems. However, its significant computational demand has limited its real-time and on-line applications, especially in embedded systems with limited computing resources, e.g., mobile robots. Heuristic methods such as the genetic algorithm (GA) based approaches have been investigated for robot path planning in dynamic environments. However, research on the simulated annealing (SA) algorithm, another popular evolutionary computation algorithm, for dynamic path planning is still limited mainly due to its high computational demand. An enhanced SA approach, which integrates two additional mathematical operators and initial path selection heuristics into the standard SA, is developed in this work for robot path planning in dynamic environments with both static and dynamic obstacles. It improves the computing performance of the standard SA significantly while giving an optimal or near-optimal robot path solution, making its real-time and on-line applications possible. Using the classic and deterministic Dijkstra algorithm as a benchmark, comprehensive case studies are carried out to demonstrate the performance of the enhanced SA and other SA algorithms in various dynamic path planning scenarios.

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Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

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The problem of estimating pseudobearing rate information of an airborne target based on measurements from a vision sensor is considered. Novel image speed and heading angle estimators are presented that exploit image morphology, hidden Markov model (HMM) filtering, and relative entropy rate (RER) concepts to allow pseudobearing rate information to be determined before (or whilst) the target track is being estimated from vision information.

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Executive Summary This project has commenced an exploration of learning and information experiences in the QUT Cube. Understanding learning in this environment has the potential to inform current implementations and future project development. In this report, we present early findings from the first phase of an investigation into what makes learning possible in the context of a giant interactive multi-media display such as the QUT Cube, which is an award-winning configuration that hosts several projects.

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Next-generation autonomous underwater vehicles (AUVs) will be required to robustly identify underwater targets for tasks such as inspection, localization, and docking. Given their often unstructured operating environments, vision offers enormous potential in underwater navigation over more traditional methods; however, reliable target segmentation often plagues these systems. This paper addresses robust vision-based target recognition by presenting a novel scale and rotationally invariant target design and recognition routine based on self-similar landmarks that enables robust target pose estimation with respect to a single camera. These algorithms are applied to an AUV with controllers developed for vision-based docking with the target. Experimental results show that the system performs exceptionally on limited processing power and demonstrates how the combined vision and controller system enables robust target identification and docking in a variety of operating conditions.

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This paper presents an account of an autonomous mobile robot deployment in a densely crowded public event with thousands of people from different age groups attending. The robot operated for eight hours on an open floor surrounded by tables, chairs and massive touchscreen displays. Due to the large number of people who were in close vicinity of the robot, different safety measures were implemented including the use of no-go zones which prevent the robot from blocking emergency exits or moving too close to the display screens. The paper presents the lessons learnt and experiences obtained from this experiment, and provides a discussion about the state of mobile service robots in such crowded environments.

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Purpose. To compare the on-road driving performance of visually impaired drivers using bioptic telescopes with age-matched controls. Methods. Participants included 23 persons (mean age = 33 ± 12 years) with visual acuity of 20/63 to 20/200 who were legally licensed to drive through a state bioptic driving program, and 23 visually normal age-matched controls (mean age = 33 ± 12 years). On-road driving was assessed in an instrumented dual-brake vehicle along 14.6 miles of city, suburban, and controlled-access highways. Two backseat evaluators independently rated driving performance using a standardized scoring system. Vehicle control was assessed through vehicle instrumentation and video recordings used to evaluate head movements, lane-keeping, pedestrian detection, and frequency of bioptic telescope use. Results. Ninety-six percent (22/23) of bioptic drivers and 100% (23/23) of controls were rated as safe to drive by the evaluators. There were no group differences for pedestrian detection, or ratings for scanning, speed, gap judgments, braking, indicator use, or obeying signs/signals. Bioptic drivers received worse ratings than controls for lane position and steering steadiness and had lower rates of correct sign and traffic signal recognition. Bioptic drivers made significantly more right head movements, drove more often over the right-hand lane marking, and exhibited more sudden braking than controls. Conclusions. Drivers with central vision loss who are licensed to drive through a bioptic driving program can display proficient on-road driving skills. This raises questions regarding the validity of denying such drivers a license without the opportunity to train with a bioptic telescope and undergo on-road evaluation.

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Intravitreal injections of GABA antagonists, dopamine agonists and brief periods of normal vision have been shown separately to inhibit form-deprivation myopia (FDM). Our study had three aims: (i) establish whether GABAergic agents modify the myopia protective effect of normal vision, (ii) investigate the receptor sub-type specificity of any observed effect, and (iii) consider an interaction with the dopamine (DA) system. Prior to the period of normal vision GABAergic agents were applied either (i) individually, (ii) in combination with other GABAergic agents (an agonist with an antagonist), or (iii) in combination with DA agonists and antagonists. Water injections were given to groups not receiving drug treatments so that all experimental eyes received intravitreal injections. As shown previously, constant form-deprivation resulted in high myopia and when diffusers were removed for 2 h per day the period of normal vision greatly reduced the FDM that developed. GABA agonists inhibited the protective effect of normal vision whereas antagonists had the opposite effect. GABAA/C agonists and D2 DA antagonists when used in combination were additive in suppressing the protective effect of normal vision. A D2 DA agonist restored some of the protective effect of normal vision that was inhibited by a GABA agonist (muscimol). The protective effect of normal vision against form-deprivation is modifiable by both the GABAergic and DAergic pathways.

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The purpose of this study is to determine visual performance in water, including the influence of pupil size. The water en-vironment was simulated by placing a goggle filled with saline in front of eyes, with apertures placed at the front of the goggle. Correction factors were determined for the different magnification under this condition in order to to estimate vision in water. Experiments were conducted on letter visual acuity (7 participants), grating resolution (8 participants), and grating contrast sensitivity (1 participant). For letter acuity, mean loss in vision in water, compared to corrected vision in air, varied between 1.1 log minutes of arc resolution (logMAR) for a 1mm aperture to 2.2 logMAR for a 7mm aperture. The vision in minutes of arc was described well by a linear relationship with pupil size. For grating acuity, mean loss varied between 1.1 logMAR for a 2mm aperture to 1.2 logMAR for a 6mm aperture. Contrast sensitivity for a 2mm aperture dete-riorated as spatial frequency increased, with 2 log unit loss by 3 cycles/degree. Superimposed on this deterioration were depressions (notches) in sensitivity, with the first three notches occurring at 0.45, 0.8 and 1.3 cycles/degree with esti-mates for water of 0.39, 0.70 and 1.13 cycles/degree. In conclusion, vision in water is poor. It becomes worse as pupil size increases, but the effects are much more marked for letter targets than for grating targets.

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Purpose: To determine visual performance in water, including the influence of pupil size. Method: The water environment was simulated by placing a goggle filled with saline in front of eyes, with apertures placed at the front of the goggle. Correction factors were determined for the different magnification under this condition to estimate vision in water. Experiments were conducted on letter visual acuity (7 participants), grating resolution (8 participants), and grating contrast sensitivity (1 participant). Results: For letter acuity, mean loss in vision in water, compared to corrected vision in air, varied between 1.1 log minutes of arc resolution (logMAR) for a 1mm aperture to 2.2 logMAR for a 7mm aperture. The vision in minutes of arc was described well by a linear relationship with pupil size. For grating acuity, mean loss varied between 1.1 logMAR for a 2mm aperture to 1.2 logMAR for a 6mm aperture. Contrast sensitivity for a 2mm aperture deteriorated as spatial frequency increased, with 2 log unit loss by 3 cycles/degree. Superimposed on this deterioration were depressions (notches) in sensitivity, with the first three notches occurring at 0.45, 0.8 and 1.3 cycles/degree and with estimates for water of 0.39, 0.70 and 1.13 cycles/degree. Conclusion: Vision in water is poor. It becomes worse as pupil size increases, but the effects are much more marked for letter targets than for grating targets.

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The process of translating research into policy and practice is not well understood. This paper uses a case study approach to interpret an example of translation with respect to theoretical approaches identified in the literature. The case study concerns research into “biological motion” or “biomotion”: when lights are placed on the moveable joints of the body and the person moves in a dark setting, there is immediate and accurate recognition of the human form although only the lights can be seen. QUT was successful in gaining Australian Research Council funding with the support of the predecessors of the Queensland Department of Transport and Main Roads (TMR) to research the biomotion effect in road worker clothing using reflective tape rather than lights, and this resulted in the incorporation of biomotion marking into AS/NZS 4602.1 2011. The most promising approach to understanding the success of this translation, SWOV’s “knowledge utilisation approach” provided some insights but was more descriptive than predictive and provided “necessary but not sufficient” conditions for translation. In particular, the supportive efforts of TMR staff engaged in the review and promulgation of national standards were critical in this case. A model of the conclusions is presented. The experiences gained in this case should provide insights into the processes involved in effectively translating research into practice.

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Novel computer vision techniques have been developed for automatic monitoring of crowed environments such as airports, railway stations and shopping malls. Using video feeds from multiple cameras, the techniques enable crowd counting, crowd flow monitoring, queue monitoring and abnormal event detection. The outcome of the research is useful for surveillance applications and for obtaining operational metrics to improve business efficiency.

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This thesis presents a novel approach to mobile robot navigation using visual information towards the goal of long-term autonomy. A novel concept of a continuous appearance-based trajectory is proposed in order to solve the limitations of previous robot navigation systems, and two new algorithms for mobile robots, CAT-SLAM and CAT-Graph, are presented and evaluated. These algorithms yield performance exceeding state-of-the-art methods on public benchmark datasets and large-scale real-world environments, and will help enable widespread use of mobile robots in everyday applications.