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Digital Sand Model using Virtual Reality Workbench

Digital Sand Model using Virtual Reality Workbench

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International Conference on computer Communication and Informatics (ICCCI)

作者： Imran A Syed V S Nageli S Sangeeta S Rakshit Computer Vision Group Centre for Artificial Intelligence and Robotics Bangalore INDIA Computer Vision Group Centre for Artificial Intelligence and Robotics Bangalore India

Sand models as used in military are thematic 3D representations of an area of interest which combined the information of maps with a more realistic 3D bird's eye view of the terrain. Sand models have been used for military planning and war gaming for many years as a field expedient, small-scale map, for planning and training of military operations. This, however increasingly fell out of favor with improved maps, aerial and satellite photography, and later, with digital terrain simulations. The proposed system, a Digital Sand Model (DSM) using a Virtual Reality (VR) Workbench, is a digital replica of the same. It involves a leader interacting with the digital environment and other viewers share his view of the digital scene. The system uses a stereoscopic projector, a mirror and Viewing Screen setup to produce a 3D stereoscopic display. This VR system allows performing interactive 3D explorations via stereo camera setup and wearable IR LEDs. A gesture recognition system is also described which allows interaction with the system. The proposed system uses Model-View-Controller (MVC) architecture as the software design.

关键词： Three dimensional displays Solid modeling Computational modeling Cameras Virtual reality Light emitting diodes computers

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Rapid shallow coastal coral reef mapping using the teardrop system

Rapid shallow coastal coral reef mapping using the teardrop ...

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OCEANS 2012 MTS/IEEE Hampton Roads Conference: Harnessing the Power of the Ocean

作者： Corpuz, Francis James Naval Jr., Prospero Capili, Eusebio Jauod, Jaylord Judilla, Roel John Soriano, Maricor Vision and Image Processing Group National Institute of Physics University of the Philippines Diliman Quezon City Philippines Computer Vision and Machine Intelligence Group Department of Computer Science University of the Philippines Diliman Quezon City Philippines Mapua Robotics Center Institutional Laboratory Mgmt Office Mapua Institute of Technology Intramuros Manila Philippines

ISBN: (纸本)9781467308298

We present a rapid shallow coastal reef mapping system using a previously developed inexpensive diver less video capture system coupled with a fast-image mosaicking technique, using an affordable GPS logging device. The system replaces the traditional manta tow system of assessing and monitoring large areas of coastal coral reefs and at the same time provides historical visual record for future references. The system utilizes Teardrop, a hollow, teardrop-shaped that houses a commercial underwater point-and-shoot camera. The camera is set to video mode and captures video of the reef while the Teardrop is being towed by a wooden fishing boat. The resulting video is parsed into frames and mosaicked by using fast image labeling. The approximate location of the mosaicked images is recorded by using an inexpensive GPS logger. The coordinates are embedded on the mosaicked images and overlaid on mapping software such as Google Earth for visual record and spatial information integration. The same points are used to compute for the total distance covered by the capturing process. The whole process from coral reef video capture to mosaicking the images and finally embedding the mosaics in mapping software can be done in as short as 1 day, providing coastal managers and local government units with a tool to rapidly visualize and monitor shallow coral reefs. © 2012 IEEE.

关键词： Mapping

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Application of computer vision and Support Vector Machines to estimate the content of impurities in olive oil samples

Application of computer vision and Support Vector Machines t...

引用

International Conference on Automation and Computing (ICAC)

作者： P. Cano Marchal D. Martínez Gila J. Gámez García J. Gómez Ortega Robotics Automation and Computer Vision Group University of Jaén Jaen Spain

The determination of the content of impurities is a very frequent analysis performed on virgin olive oil samples, but the official method established in the European norm CE 2568/91 is quite work-intensive, and it would be convenient to have an alternative approximate method to evaluate the performance of the impurity removal process. In this work we develop a system based on computer vision and pattern recognition to classify the content of impurities of the olive oil samples in three sets, indicative of the goodness of the separation process of olive oil after its extraction from the paste. Starting from the histograms of the channels of the RGB, CIELAB and HSV color spaces, we construct an initial input parameter vector and perform a feature extraction previous to the classification. Several linear and non-linear feature extraction techniques were evaluated, and the classifiers used were Support Vector Machines. The best classification rate achieved was 87.66%, obtained using KPCA and a grade-3-polynomial kernel SVM.

关键词： Feature extraction Impurities Histograms Kernel Principal component analysis Support vector machine classification

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Delayed state information filter for USBL-Aided AUV navigation

Delayed state information filter for USBL-Aided AUV navigati...

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IEEE International Conference on robotics and Automation (ICRA)

作者： David Ribas Pere Ridao Angelos Mallios Narcís Palomeras Computer Vision and Robotics group Escola Politecnica Superior University of Girona Girona Spain

This paper presents a navigation system for an Autonomous Underwater Vehicle (AUV) which merges standard dead reckoning navigation data with absolute position fixes from an Ultra-Short Base Line (USBL) system. Traditionally, the USBL transceiver is located on the surface, which makes necessary to feed the position fixes back to the AUV by means of an acoustic modem. An Information filter, which maintains a bounded circular buffer of past vehicle poses, is in charge of the sensor data fusion while dealing with the delays induced by the acoustic communication. The method is validated using a data set gathered for a dam inspection task.

关键词： Vehicles Navigation Delay Covariance matrix Vectors Robots

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Project-based learning as a motivating tool to teach computer vision

Project-based learning as a motivating tool to teach compute...

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IEEE Education Engineering (EDUCON)

作者： Rafael Garcia Nuno Gracias Computer Vision and Robotics Group University of Girona Edif. P-IV Girona Spain

This paper addresses the challenge of developing techniques for the effective teaching of computer vision. It reports on the experience of using the technique of project-based learning as a motivating method for teaching computer vision strategies within the context of a Master's program module in Visual Perception at the University of Girona (Spain). Students were asked to generate projects which involved the use of invariant features, i.e. algorithms to detect and describe local features in images. Within this project-based context, students were encouraged to search for information resources that would accompany their project ideas. Every student team was supervised by a tutoring instructor and periodic meetings were scheduled during this six-week project to follow their progress.

关键词： computer vision Educational institutions Teamwork Visual perception TV Companies

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Supervised learning of hidden and non-hidden 0-order affordances and detection in real scenes

Supervised learning of hidden and non-hidden 0-order afforda...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Aitor Aldoma Federico Tombari Markus Vincze Vision4Robotics Group Automation and Control Institute University of Technology Vienna Austria Computer Vision Lab DEIS-ARCES University of Bologna Italy

The ability to perceive possible interactions with the environment is a key capability of task-guided robotic agents. An important subset of possible interactions depends solely on the objects of interest and their position and orientation in the scene. We call these object-based interactions 0-order affordances and divide them among non-hidden and hidden whether the current configuration of an object in the scene renders its affordance directly usable or not. Conversely to other works, we propose that detecting affordances that are not directly perceivable increase the usefulness of robotic agents with manipulation capabilities, so that by appropriate manipulation they can modify the object configuration until the seeked affordance becomes available. In this paper we show how 0-order affordances depending on the geometry of the objects and their pose can be learned using a supervised learning strategy on 3D mesh representations of the objects allowing the use of the whole object geometry. Moreover, we show how the learned affordances can be detected in real scenes obtained with a low-cost depth sensor like the Microsoft Kinect through object recognition and 6D0F pose estimation and present results for both learning on meshes and detection on real scenes to demonstrate the practical application of the presented approach.

关键词： Solid modeling Robots Training Design automation Histograms Object recognition Computational modeling

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SLAM with single cluster PHD filters

SLAM with single cluster PHD filters

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IEEE International Conference on robotics and Automation (ICRA)

作者： Chee Sing Lee Daniel E. Clark Joaquim Salvi Computer Vision and Robotics Group (VICOROB) University of Girona Girona Spain Signal and Image Processing Heriot-Watt University Edinburgh UK

Recent work by Mullane, Vo, and Adams has re-examined the probabilistic foundations of feature-based Simultaneous Localization and Mapping (SLAM), casting the problem in terms of filtering with random finite sets. Algorithms were developed based on Probability Hypothesis Density (PHD) filtering techniques that provided superior performance to leading feature-based SLAM algorithms in challenging measurement scenarios with high false alarm rates, high missed detection rates, and high levels of measurement noise. We investigate this approach further by considering a hierarchical point process, or single-cluster multi-object, model, where we consider the state to consist of a map of landmarks conditioned on a vehicle state. Using Finite Set Statistics, we are able to find tractable formulae to approximate the joint vehicle-landmark state based on a single Poisson multi-object assumption on the predicted density. We describe the single-cluster PHD filter and the practical implementation developed based on a particle-system representation of the vehicle state and a Gaussian mixture approximation of the map for each particle. Synthetic simulation results are presented to compare the novel algorithm against the previous PHD filter SLAM algorithm. Results presented indicate a superior performance in vehicle and map landmark localization, and comparable performance in landmark cardinality estimation.

关键词： Simultaneous localization and mapping Filtering algorithms Prediction algorithms Weight measurement Clustering algorithms Marine animals

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Hyperspectral imaging for determination of some quality parameters for olive oil

Hyperspectral imaging for determination of some quality para...

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International Conference on Automation and Computing (ICAC)

作者： D. Martínez Gila P. Cano Marchal J. Gámez García J. Gómez Ortega Robotics Automation and Computer Vision Group Agrifood Campus of International Excellence (ceiA3) University of Jaén Jaen Spain

The analysis of the quality of a virgin olive oil involves the determination of a series of chemical indexes and organoleptic characteristics. In this work we propose an online prediction model for three chemical indexes: acidity, peroxide index and humidity content, based on an hyperspectral artificial vision system. Two methods have been developed for the construction of the model: (1) partial least squares regression (PLS) using all the captured spectral components, and (2) partial least squares regression over a subset of the components obtained applying a genetic algorithm (GA-PLS). The design and validation was carried out using olive oil samples from different seasons analysed by a renowned laboratory.

关键词： Hyperspectral imaging Predictive models Genetic algorithms Calibration Moisture Indexes Cameras

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Coral reef mosaicking using Teardrop and Fast Image Labeling

Coral reef mosaicking using Teardrop and Fast Image Labeling

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OCEANS 2012 MTS/IEEE Yeosu Conference: The Living Ocean and Coast - Diversity of Resources and Sustainable Activities

作者： Corpuz, Francis James Naval, Prospero Capili, Eusebio Jauod, Jaylord Judilla, Roel John Soriano, Maricor Vision and Image Processing Group National Institute of Physics University of the Philippines Diliman Quezon City Philippines Department of Computer Science College of Engineering University of the Philippines Diliman Quezon City Philippines Mapua Robotics Center Special Projects Laboratory Mapua Institute of Technology Intramuros Manila Philippines

ISBN: (纸本)9781457720895

In this paper, we present an inexpensive system for diverless video capture and fast image stitching of image frames for rapid reef assessment of shallow coral reefs. Our system has two main components: 1) Teardrop, a boat-towable, winged hull apparatus designed to house a commercial digital camera, and 2) a mosaicking algorithm to stitch the coral reef video into mosaics for further appreciation and analysis. The captured reef video is then separated into image frames which are to be stitched sequentially using Fast Image Labeling. The overlap between image frames is estimated using Single-Step DFT, an efficient sub-pixel estimation algorithm. The estimated overlap is used to compute for the area to be added to the mosaic space. The overlapping section between succeeding image-pairs are stitched along a seam determined by a minimal-cost path using dynamic programming. The visibility of the seam boundaries is further minimized by utilizing blending on multi-resolution splines. Experimental results on automated reef mosaics creation from actual coral reef video taken using Teardrop shows the performance of the system described. The main contribution of this work is the demonstration of a rapid reef visualization system using a diverless system and commercially available, non-research-grade imaging equipment. © 2012 IEEE.

关键词： Reefs

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Automatic seed placement for breast lesion segmentation on US images

Automatic seed placement for breast lesion segmentation on U...

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11th International Workshop on Breast Imaging, IWDM 2012

作者： Massich, Joan Meriaudeau, Fabrice Sentís, Melcior Ganau, Sergi Pérez, Elsa Martí, Robert Oliver, Arnau Martí, Joan Computer Vision and Robotics Group University of Girona Spain Laboratoire Le2i-UMR CNRS University of Burgundy Le Creusot France Department of Breast and Gynecological Radiology UDIAT-Diagnostic Center Parc Taulí Corporation Sabadell Spain Department of Radiology Hospital Josep Trueta of Girona Spain

ISBN: (纸本)9783642312700

Breast lesion boundaries have been mostly extracted by using conventional approaches as a previous step in the development of computer-aided diagnosis systems. Among these, region growing is a frequently used segmentation method. To make the segmentation completely automatic, most of the region growing methods incorporate automatic selection of the seed points. This paper proposes a new automatic seed placement algorithm for breast lesion segmentation on ultrasound images by means of assigning the probability of belonging to a lesion for every pixel depending on intensity, texture and geometrical constraints. The proposal has been evaluated using a set of sonographic breast images with accompanying expert-provided ground truth, and successfully compared to other existing algorithms. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： computer aided diagnosis

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