The proceedings contain 34 papers. The special focus in this conference is on Pattern Recognition, Artificial intelligenttechniques, Image Processing, Robotics and computervision. The topics include: Recommendation ...
ISBN:
(纸本)9783319192635
The proceedings contain 34 papers. The special focus in this conference is on Pattern Recognition, Artificial intelligenttechniques, Image Processing, Robotics and computervision. The topics include: Recommendation of process discovery algorithms through event log classification;a new method based on graph transformation for FAS mining in multi-graph collections;classification of hand movements from non-invasive brain signals using lattice neural networks with dendritic processing;a different approach for pruning micro-clusters in data stream clustering;computing constructs by using typical testor algorithms;multitask reinforcement learning in nondeterministic environments;prototype selection for graph embedding using instance selection;correlation of resampling methods for contrast pattern based classifiers;boosting the permutation based index for proximity searching;similarity analysis of archaeological potsherds using 3D surfaces;automatic detection of clouds from aerial photographs of snowy volcanoes;a comparative study of robust segmentation algorithms for iris verification system of high reliability;vision-based humanoid robot navigation in a featureless environment;evaluation of local descriptors for vision-based localization of humanoid robots;sampled weighted min-hashing for large-scale topic mining;patterns used to identify relations in corpus using formal concept analysis;improving information retrieval through a global term weighting scheme;sentiment groups as features of a classification model using a Spanish sentiment lexicon;modified binary inertial particle swarm optimization for gene selection in DNA microarray data;encoding polysomnographic signals into spike firing rate for sleep staging and patrolling routes optimization using ant colonies.
Improvements were made to the intelligence algorithms of an autonomously operating ground vehicle, Q, which competed in the 2013 intelligent Ground Vehicle Competition (IGVC). The IGVC required the vehicle to first na...
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ISBN:
(纸本)9780819499424
Improvements were made to the intelligence algorithms of an autonomously operating ground vehicle, Q, which competed in the 2013 intelligent Ground Vehicle Competition (IGVC). The IGVC required the vehicle to first navigate between two white lines on a grassy obstacle course, then pass through eight GPS waypoints, and pass through a final obstacle field. Modifications to Q included a new vision system with a more effective image processing algorithm for white line extraction. The path-planning algorithm adopted the vision system, creating smoother, more reliable navigation. With these improvements, Q successfully completed the basic autonomous navigation challenge, finishing tenth out of over 50 teams.
Service robots usually share their workspace with people. Typically, a robot's tasks require knowing when and where people are, to be able to schedule requested tasks. Therefore, there exists the need to take into...
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ISBN:
(纸本)9780819499424
Service robots usually share their workspace with people. Typically, a robot's tasks require knowing when and where people are, to be able to schedule requested tasks. Therefore, there exists the need to take into account the presence of humans when planning their actions and it is indispensable to have knowledge of robots' environments. It means in practice knowing when (time and events duration) and where (in workspace) a robot's tasks can be performed. This research paper takes steps towards obtaining of the spatial information required to execute software to plan tasks to be performed by a robot. With this aim, a program capable to define meaningful areas or zones in the robot workspace by the use of a clustering is created tied with statistically reasoned time slots when to perform each task. The software is tested using real data obtained from different cameras located along the corridors of CSE Department of University of Oulu.
Ro-Boat is an autonomous river cleaning intelligent robot incorporating mechanical design and computervision algorithm to achieve autonomous river cleaning and provide a sustainable environment. Ro-boat is designed i...
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ISBN:
(纸本)9780819499424
Ro-Boat is an autonomous river cleaning intelligent robot incorporating mechanical design and computervision algorithm to achieve autonomous river cleaning and provide a sustainable environment. Ro-boat is designed in a modular fashion with design details such as mechanical structural design, hydrodynamic design and vibrational analysis. It is incorporated with a stable mechanical system with air and water propulsion, robotic arms and solar energy source and it is proceed to become autonomous by using computervision. Both "HSV Color Space" and "SURF" are proposed to use for measurements in Kalman Filter resulting in extremely robust pollutant tracking. The system has been tested with successful results in the Yamuna River in New Delhi. We foresee that a system of Ro-boats working autonomously 24x7 can clean a major river in a city on about six months time, which is unmatched by alternative methods of river cleaning.
The intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). The IGVC is a multidisc...
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ISBN:
(纸本)9780819499424
The intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 21 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 80 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented.
This paper describes a learning assistant system using motion capture data and annotation to teach "Naginata-jutsu" (a skill to practice Japanese halberd) performance. There are some video annotation tools s...
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ISBN:
(纸本)9780819499424
This paper describes a learning assistant system using motion capture data and annotation to teach "Naginata-jutsu" (a skill to practice Japanese halberd) performance. There are some video annotation tools such as YouTube. However these video based tools have only single angle of view. Our approach that uses motion-captured data allows us to view any angle. A lecturer can write annotations related to parts of body. We have made a comparison of effectiveness between the annotation tool of YouTube and the proposed system. The experimental result showed that our system triggered more annotations than the annotation tool of YouTube.
Underwater environments present a considerable challenge for computervision, since water is a scattering medium with substantial light absorption characteristics which is made even more severe by turbidity. This pose...
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Underwater environments present a considerable challenge for computervision, since water is a scattering medium with substantial light absorption characteristics which is made even more severe by turbidity. This poses significant problems for visual underwater navigation, object detection, tracking and recognition. Previous works tackle the problem by using unreliable priors or expensive and complex devices. This paper adopts a physical underwater light attenuation model which is used to enhance the quality of images and enable the applicability of traditional computervisiontechniques images acquired from underwater scenes. The proposed method simultaneously estimates the attenuation parameter of the medium and the depth map of the scene to compute the image irradiance thus reducing the effect of the medium in the images. Our approach is based on a novel optical flow method, which is capable of dealing with scattering media, and a new technique that robustly estimates the medium parameters. Combined with structure-from-motion techniques, the depth map is estimated and a model-based restoration is performed. The method was tested both with simulated and real sequences of images. The experimental images were acquired with a camera mounted on a Remotely Operated Vehicle (ROV) navigating in a naturally lit, shallow seawater. The results show that the proposed technique allows for substantial restoration of the images, thereby improving the ability to identify and match features, which in turn is an essential step for other computervisionalgorithms such as object detection and tracking, and autonomous navigation.
In a milking robot, the correct localization and positioning of milking teat cups is of very high importance. The milking robots technology has not changed since a decade and is based primarily on laser profiles for t...
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ISBN:
(纸本)9780819499424
In a milking robot, the correct localization and positioning of milking teat cups is of very high importance. The milking robots technology has not changed since a decade and is based primarily on laser profiles for teats approximate positions estimation. This technology has reached its limit and does not allow optimal positioning of the milking cups. Also, in the presence of occlusions, the milking robot fails to milk the cow. These problems, have economic consequences for producers and animal health (e.g. development of mastitis). To overcome the limitations of current robots, we have developed a new system based on 3D vision, capable of efficiently positioning the milking cups. A prototype of an intelligent robot system based on 3D vision for real- time positioning of a milking robot has been built and tested under various conditions on a synthetic udder model (in static and moving scenarios). Experimental tests, were performed using 3D Time-Of-Flight (TOF) and RGBD cameras. The proposed algorithms permit the online segmentation of teats by combing 2D and 3D visual information. The obtained results permit the teat 3D position computation. This information is then sent to the milking robot for teat cups positioning. The vision system has a real-time performance and monitors the optimal positioning of the cups even in the presence of motion. The obtained results, with both TOF and RGBD cameras, show the good performance of the proposed system. The best performance was obtained with RGBD cameras. This latter technology will be used in future real life experimental tests.
This paper describes two methods for estimating the minimum and maximum curvatures for a 3D surface and compares the computational efficiency of these approaches on 3D sensor data. The classical method of Least Square...
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ISBN:
(纸本)9780819499424
This paper describes two methods for estimating the minimum and maximum curvatures for a 3D surface and compares the computational efficiency of these approaches on 3D sensor data. The classical method of Least Square Fitting (LSF) finds an approximation of a cubic polynomial fit for the local surface around the point of interest P and uses the coefficients to compute curvatures. The Discrete Differential Geometry (DDG) algorithm approximates a triangulation of the surface around P and calculates the angle deficit at P as an estimate of the curvatures. The accuracy and speed of both algorithms are compared by applying them to synthetic and real data sets with sampling neighborhoods of varying sizes. Our results indicate that the LSF and DDG methods produce comparable results for curvature estimations but the DDG method performs two orders of magnitude faster, on average. However, the DDG algorithm is more susceptible to noise because it does not smooth the data as well as the LSF method. In applications where it is not necessary for the curvatures to be precise (such as estimating anchor point locations for face recognition) the DDG method yields similar results to the LSF method while performing much more efficiently.
In this paper, development of a low-cost PID controller with an intelligent behavior coordination system for an autonomous mobile robot is described that is equipped with IR sensors, ultrasonic sensors, regulator, and...
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ISBN:
(纸本)9780819499424
In this paper, development of a low-cost PID controller with an intelligent behavior coordination system for an autonomous mobile robot is described that is equipped with IR sensors, ultrasonic sensors, regulator, and RC filters on the robot platform based on HCS12 microcontroller and embedded systems. A novel hybrid PID controller and behavior coordination system is developed for wall-following navigation and obstacle avoidance of an autonomous mobile robot. Adaptive control used in this robot is a hybrid PID algorithm associated with template and behavior coordination models. Software development contains motor control, behavior coordination intelligent system and sensor fusion. In addition, the module-based programming technique is adopted to improve the efficiency of integrating the hybrid PID and template as well as behavior coordination model algorithms. The hybrid model is developed to synthesize PID control algorithms, template and behavior coordination technique for wall-following navigation with obstacle avoidance systems. The motor control, obstacle avoidance, and wall-following navigation algorithms are developed to propel and steer the autonomous mobile robot. Experiments validate how this PID controller and behavior coordination system directs an autonomous mobile robot to perform wall-following navigation with obstacle avoidance. Hardware configuration and module-based technique are described in this paper. Experimental results demonstrate that the robot is successfully capable of being guided by the hybrid PID controller and behavior coordination system for wall-following navigation with obstacle avoidance.
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