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Start date: 2010 × End date: 2018 × Author: Brunet, Pere ×

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Now showing 1 - 6 of 6
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    Surfel Octrees: A New Scheme for Interactive Inspection of Anatomy Atlases in Client-Server Applications
    (The Eurographics Association, 2015) Surinyac, Jordi; Brunet, Pere; Mateu Sbert and Jorge Lopez-Moreno
    Nowadays, an increasing interest on tele-medicine and tele-diagnostic solutions can be observed, with client/server architectures for remote inspection of volume image-based medical data which are becoming more and more popular. The use of portable devices is gradually spreading due to their portability and easy maintenance. In this paper, we present an efficient data model for segmented volume models based on a hierarchical data structure of surfels per anatomical structure. Surfel Octrees are compact enough for transmission through networks with limited bandwidth, and provide good visual quality in the client devices at a limited footprint. Anatomy atlases are represented as octree forests, supporting local interaction in the client device and selection of groups of medical organs. After presenting the octree generation and interaction algorithms, we present several examples and discuss the interest of the proposed approach in low-end devices such as mobiles and tablets.
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    Downsampling and Storage of Pre-Computed Gradients for Volume Rendering
    (The Eurographics Association, 2017) Díaz-García, Jesús; Brunet, Pere; Navazo, Isabel; Vázquez, Pere-Pau; Fco. Javier Melero and Nuria Pelechano
    The way in which gradients are computed in volume datasets influences both the quality of the shading and the performance obtained in rendering algorithms. In particular, the visualization of coarse datasets in multi-resolution representations is affected when gradients are evaluated on-the-fly in the shader code by accessing neighbouring positions. This is not only a costly computation that compromises the performance of the visualization process, but also one that provides gradients of low quality that do not resemble the originals as much as desired because of the new topology of downsampled datasets. An obvious solution is to pre-compute the gradients and store them. Unfortunately, this originates two problems: First, the downsampling process, that is also prone to generate artifacts. Second, the limited bit size of storage itself causes the gradients to loss precision. In order to solve these issues, we propose a downsampling filter for pre-computed gradients that provides improved gradients that better match the originals such that the aforementioned artifacts disappear. Secondly, to address the storage problem, we present a method for the efficient storage of gradient directions that is able to minimize the minimum angle achieved among all representable vectors in a space of 3 bytes. We also provide several examples that show the advantages of the proposed approaches.
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    VR-assisted Architectural Design in a Heritage Site: the Sagrada Família Case Study
    (The Eurographics Association, 2018) Andujar, Carlos; Brunet, Pere; Buxareu, Jerónimo; Fons, Joan; Laguarda, Narcís; Pascual, Jordi; Pelechano, Nuria; Sablatnig, Robert and Wimmer, Michael
    Virtual Reality (VR) simulations have long been proposed to allow users to explore both yet-to-built buildings in architectural design, and ancient, remote or disappeared buildings in cultural heritage. In this paper we describe an on-going VR project on an UNESCO World Heritage Site that simultaneously addresses both scenarios: supporting architects in the task of designing the remaining parts of a large unfinished building, and simulating existing parts that define the environment that new designs must conform to. The main challenge for the team of architects is to advance towards the project completion being faithful to the original Gaudí's project, since many plans, drawings and plaster models were lost. We analyze the main requirements for collaborative architectural design in such a unique scenario, describe the main technical challenges, and discuss the lessons learned after one year of use of the system.
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    Depth Map Repairing for Building Reconstruction
    (The Eurographics Association, 2018) Andújar, Carlos; Argudo, Oscar; Besora, Isaac; Brunet, Pere; Chica, Antoni; Comino Trinidad, Marc; García-Fernández, Ignacio and Ureña, Carlos
    Structure-from-motion along with multi-view stereo techniques jointly allow for the inexpensive scanning of 3D objects (e.g. buildings) using just a collection of images taken from commodity cameras. Despite major advances in these fields, a major limitation of dense reconstruction algorithms is that correct depth/normal values are not recovered on specular surfaces (e.g. windows) and parts lacking image features (e.g. flat, textureless parts of the facade). Since these reflective properties are inherent to the surface being acquired, images from different viewpoints hardly contribute to solve this problem. In this paper we present a simple method for detecting, classifying and filling non-valid data regions in depth maps produced by dense stereo algorithms. Triangles meshes reconstructed from our repaired depth maps exhibit much higher quality than those produced by state-of-the-art reconstruction algorithms like Screened Poisson-based techniques.
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    Sensor-aware Normal Estimation for Point Clouds from 3D Range Scans
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Comino Trinidad, Marc; Andujar, Carlos; Chica, Antonio; Brunet, Pere; Ju, Tao and Vaxman, Amir
    Normal vectors are essential for many point cloud operations, including segmentation, reconstruction and rendering. The robust estimation of normal vectors from 3D range scans is a challenging task due to undersampling and noise, specially when combining points sampled from multiple sensor locations. Our error model assumes a Gaussian distribution of the range error with spatially-varying variances that depend on sensor distance and reflected intensity, mimicking the features of Lidar equipment. In this paper we study the impact of measurement errors on the covariance matrices of point neighborhoods. We show that covariance matrices of the true surface points can be estimated from those of the acquired points plus sensordependent directional terms. We derive a lower bound on the neighbourhood size to guarantee that estimated matrix coefficients will be within a predefined error with a prescribed probability. This bound is key for achieving an optimal trade-off between smoothness and fine detail preservation. We also propose and compare different strategies for handling neighborhoods with samples coming from multiple materials and sensors. We show analytically that our method provides better normal estimates than competing approaches in noise conditions similar to those found in Lidar equipment.
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    Ventricular Puncture Trainer
    (The Eurographics Association, 2012) Pandiella, Imanol Muñoz; Monclús, Eva; Brunet, Pere; Conesa, Gerard; Isabel Navazo and Gustavo Patow
    The learning process in neurosurgery is a large and difficult task based on experimentation, being ventriculostomy not an exception. We have developed a virtual reality system to help training novel surgeons on this kind of operation. The system consists of the simulation of the surgery using a haptic device and a subsequent 3D visual inspection of the surgical trajectory. Our main objective was to proof that the tactile sensation produced by our system was enough realistic for the surgeons. We carried out a demonstration session in a medical workshop where all surgeons attending the workshop used the system with a very enthusiastic response about the perception experimented through the system.