GASP : Geometric Association with Surface Patches

A fundamental challenge to sensory processing tasks in perception and robotics is the problem of obtaining data associations across views. We present a robust solution for ascertaining potentially dense surface patch (superpixel) associations, requiring just range information. Our approach involves decomposition of a view into regularized surface patches. We represent them as sequences expressing geometry invariantly over their superpixel neighborhoods, as uniquely consistent partial orderings. We match these representations through an optimal sequence comparison metric based on the Damerau-Levenshtein distance - enabling robust association with quadratic complexity (in contrast to hitherto employed joint matching formulations which are NP-complete). The approach is able to perform under wide baselines, heavy rotations, partial overlaps, significant occlusions and sensor noise. The technique does not require any priors -- motion or otherwise, and does not make restrictive assumptions on scene structure and sensor movement. It does not require appearance -- is hence more widely applicable than appearance reliant methods, and invulnerable to related ambiguities such as textureless or aliased content. We present promising qualitative and quantitative results under diverse settings, along with comparatives with popular approaches based on range as well as RGB-D data.Comment: International Conference on 3D Vision, 201

Management and Service-aware Networking Architectures (MANA) for Future Internet Position Paper: System Functions, Capabilities and Requirements

Future Internet (FI) research and development threads have recently been gaining momentum all over the world and as such the international race to create a new generation Internet is in full swing: GENI, Asia Future Internet, Future Internet Forum Korea, European Union Future Internet Assembly (FIA). This is a position paper identifying the research orientation with a time horizon of 10 years, together with the key challenges for the capabilities in the Management and Service-aware Networking Architectures (MANA) part of the Future Internet (FI) allowing for parallel and federated Internet(s)

Study of Subjective and Objective Quality Evaluation of 3D Point Cloud Data by the JPEG Committee

The SC29/WG1 (JPEG) Committee within ISO/IEC is currently working on developing standards for the storage, compression and transmission of 3D point cloud information. To support the creation of these standards, the committee has created a database of 3D point clouds representing various quality levels and use-cases and examined a range of 2D and 3D objective quality measures. The examined quality measures are correlated with subjective judgments for a number of compression levels. In this paper we describe the database created, tests performed and key observations on the problems of 3D point cloud quality assessment

MODELING OF ROOFS FROM POINT CLOUDS USING GENETIC ALGORITHMS

Building roof extraction has been studied for more than thirty years and it generates models that provide important information for many applications, especially urban planning. The present work aimed to model roofs only from point clouds using genetic algorithms (GAs) to develop a more automatized and efficient method. For this, firstly, an algorithm for edge detection was developed. Experiments were performed with simulated and real point clouds, obtained by LIDAR. In the experiments with simulated point clouds, three types of point clouds with different complexities were created, and the effects of noise and scan line spacing on the results were evaluated. For the experiments with real point clouds, five roofs were chosen as examples, each with a different characteristic. GAs were used to select, among the points identified during edge detection, the so-called ‘significant points’, those which are essential to the accurate reconstruction of the roof model. These points were then used to generate the models, which were assessed qualitatively and quantitatively. Such evaluations showed that the use of GAs proved to be efficient for the modeling of roofs, as the model geometry was satisfactory, the error was within an acceptable range, and the computational effort was clearly reduced

The Thunderstorm and Its Phenomena

n/

Geometric 3D point cloud compression

The use of 3D data in mobile robotics applications provides valuable information about the robot’s environment but usually the huge amount of 3D information is unmanageable by the robot storage and computing capabilities. A data compression is necessary to store and manage this information but preserving as much information as possible. In this paper, we propose a 3D lossy compression system based on plane extraction which represent the points of each scene plane as a Delaunay triangulation and a set of points/area information. The compression system can be customized to achieve different data compression or accuracy ratios. It also supports a color segmentation stage to preserve original scene color information and provides a realistic scene reconstruction. The design of the method provides a fast scene reconstruction useful for further visualization or processing tasks.This work has been supported by the Spanish Government DPI2013-40534-R grant