540 research outputs found

    Line Based Trinocular Stereo

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    An approach to solving the stereo correspondence problem in trinocular stereo vision is described. It is based on geometric matching constraints relating the orientation of lines extracted in three images taken from different viewpoints. These novel constraints are termed unary orientation and binary orientation constraints. Matching is achieved within an optimisation framework in which the constraints are encoded into a cost function that is optimised using the simulated annealing method. Results are demonstrated and the characteristics of the approach are explored on both synthetic and real 1 trinocular images.

    Semantizing Complex 3D Scenes using Constrained Attribute Grammars

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    International audienceWe propose a new approach to automatically semantize complex objects in a 3D scene. For this, we define an expressive formalism combining the power of both attribute grammars and constraint. It offers a practical conceptual interface, which is crucial to write large maintainable specifications. As recursion is inadequate to express large collections of items, we introduce maximal operators, that are essential to reduce the parsing search space. Given a grammar in this formalism and a 3D scene, we show how to automatically compute a shared parse forest of all interpretations -- in practice, only a few, thanks to relevant constraints. We evaluate this technique for building model semantization using CAD model examples as well as photogrammetric and simulated LiDAR data

    Recognition of three dimensional objects using deformable models

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    Fully-Functional Suffix Trees and Optimal Text Searching in BWT-runs Bounded Space

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    Indexing highly repetitive texts - such as genomic databases, software repositories and versioned text collections - has become an important problem since the turn of the millennium. A relevant compressibility measure for repetitive texts is r, the number of runs in their Burrows-Wheeler Transforms (BWTs). One of the earliest indexes for repetitive collections, the Run-Length FM-index, used O(r) space and was able to efficiently count the number of occurrences of a pattern of length m in the text (in loglogarithmic time per pattern symbol, with current techniques). However, it was unable to locate the positions of those occurrences efficiently within a space bounded in terms of r. In this paper we close this long-standing problem, showing how to extend the Run-Length FM-index so that it can locate the occ occurrences efficiently within O(r) space (in loglogarithmic time each), and reaching optimal time, O(m + occ), within O(r log log w ({\sigma} + n/r)) space, for a text of length n over an alphabet of size {\sigma} on a RAM machine with words of w = {\Omega}(log n) bits. Within that space, our index can also count in optimal time, O(m). Multiplying the space by O(w/ log {\sigma}), we support count and locate in O(dm log({\sigma})/we) and O(dm log({\sigma})/we + occ) time, which is optimal in the packed setting and had not been obtained before in compressed space. We also describe a structure using O(r log(n/r)) space that replaces the text and extracts any text substring of length ` in almost-optimal time O(log(n/r) + ` log({\sigma})/w). Within that space, we similarly provide direct access to suffix array, inverse suffix array, and longest common prefix array cells, and extend these capabilities to full suffix tree functionality, typically in O(log(n/r)) time per operation.Comment: submitted version; optimal count and locate in smaller space: O(r log log_w(n/r + sigma)

    Cylinders extraction in non-oriented point clouds as a clustering problem

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    Finding geometric primitives in 3D point clouds is a fundamental task in many engineering applications such as robotics, autonomous-vehicles and automated industrial inspection. Among all solid shapes, cylinders are frequently found in a variety of scenes, comprising natural or man-made objects. Despite their ubiquitous presence, automated extraction and fitting can become challenging if performed ”in-the-wild”, when the number of primitives is unknown or the point cloud is noisy and not oriented. In this paper we pose the problem of extracting multiple cylinders in a scene by means of a Game-Theoretic inlier selection process exploiting the geometrical relations between pairs of axis candidates. First, we formulate the similarity between two possible cylinders considering the rigid motion aligning the two axes to the same line. This motion is represented with a unitary dual-quaternion so that the distance between two cylinders is induced by the length of the shortest geodesic path in SE(3). Then, a Game-Theoretical process exploits such similarity function to extract sets of primitives maximizing their inner mutual consensus. The outcome of the evolutionary process consists in a probability distribution over the sets of candidates (ie axes), which in turn is used to directly estimate the final cylinder parameters. An extensive experimental section shows that the proposed algorithm offers a high resilience to noise, since the process inherently discards inconsistent data. Compared to other methods, it does not need point normals and does not require a fine tuning of multiple parameters

    Analysis and development of the Bees Algorithm for primitive fitting in point cloud models

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    This work addresses the problem of fitting a geometrical primitive to a point cloud as a numerical optimisation problem. Intelligent Optimisation Techniques like Evolutionary Algorithms and the Bees Algorithm were here adapted to select the most fit primitive out of a population of solutions, and the results compared. The necessity of understanding the dynamics of the Bees Algorithm to improve its performances and applicability led to an in-depth analysis of its key parts. A new mathematical definition of the algorithm led to the discovery and formalisation of several properties, many of which provided a mathematical answer to behaviours so far only observed in empirical tests. The implications of heuristics commonly used in the Bees Algorithm, like site abandonment and neighbourhood shrinking, were statistically analysed. The probability of a premature stalling of the local search at a site has been quantified under certain conditions. The effect of the choice of shape for the local neighbourhood on the exploitative search of the Bees Algorithm was analysed. The study revealed that this commonly overlooked aspect has profound consequences on the effectiveness of the local search, and practical applications have been suggested to address specific search problems. The results of the primitive fitting study, and the analysis of the Bees Algorithm, inspired the creation of a new algorithm for problems where multiple solutions are sought (multi-solution optimisation). This new algorithm is an ex- tension of the Bees Algorithm to multi-solution optimisation. It uses topological information on the search space gathered during the cycles of local search at a site, which is normally discarded, to alter the fitness function. The function is altered to discourage further search in already explored regions of the fitness landscape, and force the algorithm to discover new optima. This new algorithm found immediate application on the multi-shape variant of the primitive fitting problem. In a series of experimental tests, the new algorithm obtained promising results, showing its ability to find many shapes in a point cloud. It also showed its suitability as a general technique for the multi-solution optimisation problem

    Learning Visual Patterns: Imposing Order on Objects, Trajectories and Networks

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    Fundamental to many tasks in the field of computer vision, this work considers the understanding of observed visual patterns in static images and dynamic scenes . Within this broad domain, we focus on three particular subtasks, contributing novel solutions to: (a) the subordinate categorization of objects (avian species specifically), (b) the analysis of multi-agent interactions using the agent trajectories, and (c) the estimation of camera network topology. In contrast to object recognition, where the presence or absence of certain parts is generally indicative of basic-level category, the problem of subordinate categorization rests on the ability to establish salient distinctions amongst the characteristics of those parts which comprise the basic-level category. Focusing on an avian domain due to the fine-grained structure of the category taxonomy, we explore a pose-normalized appearance model based on a volumetric poselet scheme. The variation in shape and appearance properties of these parts across a taxonomy provides the cues needed for subordinate categorization. Our model associates the underlying image pattern parameters used for detection with corresponding volumetric part location, scale and orientation parameters. These parameters implicitly define a mapping from the image pixels into a pose-normalized appearance space, removing view and pose dependencies, facilitating fine-grained categorization with relatively few training examples. We next examine the problem of leveraging trajectories to understand interactions in dynamic multi-agent environments. We focus on perceptual tasks, those for which an agent's behavior is governed largely by the individuals and objects around them. We introduce kinetic accessibility, a model for evaluating the perceived, and thus anticipated, movements of other agents. This new model is then applied to the analysis of basketball footage. The kinetic accessibility measures are coupled with low-level visual cues and domain-specific knowledge for determining which player has possession of the ball and for recognizing events such as passes, shots and turnovers. Finally, we present two differing approaches for estimating camera network topology. The first technique seeks to partition a set of observations made in the camera network into individual object trajectories. As exhaustive consideration of the partition space is intractable, partitions are considered incrementally, adding observations while pruning unlikely partitions. Partition likelihood is determined by the evaluation of a probabilistic graphical model, balancing the consistency of appearances across a hypothesized trajectory with the latest predictions of camera adjacency. A primarily benefit of estimating object trajectories is that higher-order statistics, as opposed to just first-order adjacency, can be derived, yielding resilience to camera failure and the potential for improved tracking performance between cameras. Unlike the former centralized technique, the latter takes a decentralized approach, estimating the global network topology with local computations using sequential Bayesian estimation on a modified multinomial distribution. Key to this method is an information-theoretic appearance model for observation weighting. The inherently distributed nature of the approach allows the simultaneous utilization of all sensors as processing agents in collectively recovering the network topology

    Extraction robuste de primitives géométriques 3D dans un nuage de points et alignement basé sur les primitives

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    Dans ce projet, nous Ă©tudions les problĂšmes de rĂ©tro-ingĂ©nierie et de contrĂŽle de la qualitĂ© qui jouent un rĂŽle important dans la fabrication industrielle. La rĂ©tro-ingĂ©nierie tente de reconstruire un modĂšle 3D Ă  partir de nuages de points, qui s’apparente au problĂšme de la reconstruction de la surface 3D. Le contrĂŽle de la qualitĂ© est un processus dans lequel la qualitĂ© de tous les facteurs impliquĂ©s dans la production est abordĂ©e. En fait, les systĂšmes ci-dessus nĂ©cessitent beaucoup d’intervention de la part d’un utilisateur expĂ©rimentĂ©, rĂ©sultat souhaitĂ© est encore loin soit une automatisation complĂšte du processus. Par consĂ©quent, de nombreux dĂ©fis doivent encore ĂȘtre abordĂ©s pour atteindre ce rĂ©sultat hautement souhaitable en production automatisĂ©e. La premiĂšre question abordĂ©e dans la thĂšse consiste Ă  extraire les primitives gĂ©omĂ©triques 3D Ă  partir de nuages de points. Un cadre complet pour extraire plusieurs types de primitives Ă  partir de donnĂ©es 3D est proposĂ©. En particulier, une nouvelle mĂ©thode de validation est proposĂ©e pour Ă©valuer la qualitĂ© des primitives extraites. À la fin, toutes les primitives prĂ©sentes dans le nuage de points sont extraites avec les points de donnĂ©es associĂ©s et leurs paramĂštres descriptifs. Ces rĂ©sultats pourraient ĂȘtre utilisĂ©s dans diverses applications telles que la reconstruction de scĂšnes on d’édifices, la gĂ©omĂ©trie constructive et etc. La seconde question traiĂ©e dans ce travail porte sur l’alignement de deux ensembles de donnĂ©es 3D Ă  l’aide de primitives gĂ©omĂ©triques, qui sont considĂ©rĂ©es comme un nouveau descripteur robuste. L’idĂ©e d’utiliser les primitives pour l’alignement arrive Ă  surmonter plusieurs dĂ©fis rencontrĂ©s par les mĂ©thodes d’alignement existantes. Ce problĂšme d’alignement est une Ă©tape essentielle dans la modĂ©lisation 3D, la mise en registre, la rĂ©cupĂ©ration de modĂšles. Enfin, nous proposons Ă©galement une mĂ©thode automatique pour extraire les discontinutĂ©s Ă  partir de donnĂ©es 3D d’objets manufacturĂ©s. En intĂ©grant ces discontinutĂ©s au problĂšme d’alignement, il est possible d’établir automatiquement les correspondances entre primitives en utilisant l’appariement de graphes relationnels avec attributs. Nous avons expĂ©rimentĂ© tous les algorithmes proposĂ©s sur diffĂ©rents jeux de donnĂ©es synthĂ©tiques et rĂ©elles. Ces algorithmes ont non seulement rĂ©ussi Ă  accomplir leur tĂąches avec succĂšs mais se sont aussi avĂ©rĂ©s supĂ©rieus aux mĂ©thodes proposĂ©es dans la literature. Les rĂ©sultats prĂ©sentĂ©s dans le thĂšse pourraient s’avĂ©rĂ©r utilises Ă  plusieurs applications.In this research project, we address reverse engineering and quality control problems that play significant roles in industrial manufacturing. Reverse engineering attempts to rebuild a 3D model from the scanned data captured from a object, which is the problem similar to 3D surface reconstruction. Quality control is a process in which the quality of all factors involved in production is monitored and revised. In fact, the above systems currently require significant intervention from experienced users, and are thus still far from being fully automated. Therefore, many challenges still need to be addressed to achieve the desired performance for automated production. The first proposition of this thesis is to extract 3D geometric primitives from point clouds for reverse engineering and surface reconstruction. A complete framework to extract multiple types of primitives from 3D data is proposed. In particular, a novel validation method is also proposed to assess the quality of the extracted primitives. At the end, all primitives present in the point cloud are extracted with their associated data points and descriptive parameters. These results could be used in various applications such as scene and building reconstruction, constructive solid geometry, etc. The second proposition of the thesis is to align two 3D datasets using the extracted geometric primitives, which is introduced as a novel and robust descriptor. The idea of using primitives for alignment is addressed several challenges faced by existing registration methods. This alignment problem is an essential step in 3D modeling, registration and model retrieval. Finally, an automatic method to extract sharp features from 3D data of man-made objects is also proposed. By integrating the extracted sharp features into the alignment framework, it is possible implement automatic assignment of primitive correspondences using attribute relational graph matching. Each primitive is considered as a node of the graph and an attribute relational graph is created to provide a structural and relational description between primitives. We have experimented all the proposed algorithms on different synthetic and real scanned datasets. Our algorithms not only are successful in completing their tasks with good results but also outperform other methods. We believe that the contribution of them could be useful in many applications
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