自由曲面透明体的非接触厚度测量

针对自由曲面透明体厚度测量,提出一种基于结构光机理的3D 视觉测量方法和系统结构,介绍了该方法的基本原理和测量系统实现技术,并给出了部分实验,证实了该方法的有效性。

Reconstruction active par projection de lumière non structurée

Cette thèse porte sur la reconstruction active de modèles 3D à l’aide d’une caméra et d’un projecteur. Les méthodes de reconstruction standards utilisent des motifs de lumière codée qui ont leurs forces et leurs faiblesses. Nous introduisons de nouveaux motifs basés sur la lumière non structurée afin de pallier aux manques des méthodes existantes. Les travaux présentés s’articulent autour de trois axes : la robustesse, la précision et finalement la comparaison des patrons de lumière non structurée aux autres méthodes. Les patrons de lumière non structurée se différencient en premier lieu par leur robustesse aux interréflexions et aux discontinuités de profondeur. Ils sont conçus de sorte à homogénéiser la quantité d’illumination indirecte causée par la projection sur des surfaces difficiles. En contrepartie, la mise en correspondance des images projetées et capturées est plus complexe qu’avec les méthodes dites structurées. Une méthode d’appariement probabiliste et efficace est proposée afin de résoudre ce problème. Un autre aspect important des reconstructions basées sur la lumière non structurée est la capacité de retrouver des correspondances sous-pixels, c’est-à-dire à un niveau de précision plus fin que le pixel. Nous présentons une méthode de génération de code de très grande longueur à partir des motifs de lumière non structurée. Ces codes ont l’avantage double de permettre l’extraction de correspondances plus précises tout en requérant l’utilisation de moins d’images. Cette contribution place notre méthode parmi les meilleures au niveau de la précision tout en garantissant une très bonne robustesse. Finalement, la dernière partie de cette thèse s’intéresse à la comparaison des méthodes existantes, en particulier sur la relation entre la quantité d’images projetées et la qualité de la reconstruction. Bien que certaines méthodes nécessitent un nombre constant d’images, d’autres, comme la nôtre, peuvent se contenter d’en utiliser moins aux dépens d’une qualité moindre. Nous proposons une méthode simple pour établir une correspondance optimale pouvant servir de référence à des fins de comparaison. Enfin, nous présentons des méthodes hybrides qui donnent de très bons résultats avec peu d’images.

Modelling human visual navigation using multi-view scene reconstruction

It is often assumed that humans generate a 3D reconstruction of the environment, either in egocentric or world-based coordinates, but the steps involved are unknown. Here, we propose two reconstruction-based models, evaluated using data from two tasks in immersive virtual reality. We model the observer’s prediction of landmark location based on standard photogrammetric methods and then combine location predictions to compute likelihood maps of navigation behaviour. In one model, each scene point is treated independently in the reconstruction; in the other, the pertinent variable is the spatial relationship between pairs of points. Participants viewed a simple environment from one location, were transported (virtually) to another part of the scene and were asked to navigate back. Error distributions varied substantially with changes in scene layout; we compared these directly with the likelihood maps to quantify the success of the models. We also measured error distributions when participants manipulated the location of a landmark to match the preceding interval, providing a direct test of the landmark-location stage of the navigation models. Models such as this, which start with scenes and end with a probabilistic prediction of behaviour, are likely to be increasingly useful for understanding 3D vision.

A moving observer in a three-dimensional world

For many tasks, such as retrieving a previously viewed object, an observer must form a representation of the world at one location and use it at another. A world-based 3D reconstruction of the scene built up from visual information would fulfil this requirement, something computer vision now achieves with great speed and accuracy. However, I argue that it is neither easy nor necessary for the brain to do this. I discuss biologically plausible alternatives, including the possibility of avoiding 3D coordinate frames such as ego-centric and world-based representations. For example, the distance, slant and local shape of surfaces dictate the propensity of visual features to move in the image with respect to one another as the observer’s perspective changes (through movement or binocular viewing). Such propensities can be stored without the need for 3D reference frames. The problem of representing a stable scene in the face of continual head and eye movements is an appropriate starting place for understanding the goal of 3D vision, more so, I argue, than the case of a static binocular observer.

Duoscope

The ambiguous representation of spatial depth in Thornton Walker’s painting The Homage creates a peculiar sense in which the ‘whereness’ of depicted objects and atmosphere cannot be ascertained by, either perspectival convention or perceptual strategies. This visual-spatial ambiguity resonates with my interested in ‘broken’ stereography. Hence, ‘duoscopy’ refers to the limitations of binocular vision when the object of perception is itself duplicitous.

An autostereoscopic device for mobile applications based on a liquid crystal microlens array and an OLED display

In recent years, many experimental and theoretical research groups worldwide have actively worked on demonstrating the use of liquid crystals (LCs) as adaptive lenses for image generation, waveform shaping, and non-mechanical focusing applications. In particular, important achievements have concerned the development of alternative solutions for 3D vision. This work focuses on the design and evaluation of the electro-optic response of a LC-based 2D/3D autostereoscopic display prototype. A strategy for achieving 2D/3D vision has been implemented with a cylindrical LC lens array placed in front of a display; this array acts as a lenticular sheet with a tunable focal length by electrically controlling the birefringence. The performance of the 2D/3D device was evaluated in terms of the angular luminance, image deflection, crosstalk, and 3D contrast within a simulated environment. These measurements were performed with characterization equipment for autostereoscopic 3D displays (angular resolution of 0.03 ).

A Performance Evaluation of Surface Normals-Based Descriptors for Recognition of Objects using CAD-Models

This paper describes a study and analysis of surface normal-base descriptors for 3D object recognition. Specifically, we evaluate the behaviour of descriptors in the recognition process using virtual models of objects created from CAD software. Later, we test them in real scenes using synthetic objects created with a 3D printer from the virtual models. In both cases, the same virtual models are used on the matching process to find similarity. The difference between both experiments is in the type of views used in the tests. Our analysis evaluates three subjects: the effectiveness of 3D descriptors depending on the viewpoint of camera, the geometry complexity of the model and the runtime used to do the recognition process and the success rate to recognize a view of object among the models saved in the database.

Using a RGB-D camera for 6DoF SLAM

This paper presents a method for fast calculation of the egomotion done by a robot using visual features. The method is part of a complete system for automatic map building and Simultaneous Localization and Mapping (SLAM). The method uses optical flow in order to determine if the robot has done a movement. If so, some visual features which do not accomplish several criteria (like intersection, unicity, etc,) are deleted, and then the egomotion is calculated. We use a state-of-the-art algorithm (TORO) in order to rectify the map and solve the SLAM problem. The proposed method provides better efficiency that other current methods.

An improvement of a SLAM RGB-D method with movement prediction derived from a study of visual features

This paper presents a method for the fast calculation of a robot’s egomotion using visual features. The method is part of a complete system for automatic map building and Simultaneous Location and Mapping (SLAM). The method uses optical flow to determine whether the robot has undergone a movement. If so, some visual features that do not satisfy several criteria are deleted, and then egomotion is calculated. Thus, the proposed method improves the efficiency of the whole process because not all the data is processed. We use a state-of-the-art algorithm (TORO) to rectify the map and solve the SLAM problem. Additionally, a study of different visual detectors and descriptors has been conducted to identify which of them are more suitable for the SLAM problem. Finally, a navigation method is described using the map obtained from the SLAM solution.

Sistema di visione stereo su architettura ZYNQ

Lo scopo della tesi è creare un’architettura in FPGA in grado di ricavare informazioni 3D da una coppia di sensori stereo. La pipeline è stata realizzata utilizzando il System-on-Chip Zynq, che permette una stretta interazione tra la parte hardware realizzata in FPGA e la CPU. Dopo uno studio preliminare degli strumenti hardware e software, è stata realizzata l’architettura base per la scrittura e la lettura di immagini nella memoria DDR dello Zynq. In seguito l’attenzione si è spostata sull’implementazione di algoritmi stereo (rettificazione e stereo matching) su FPGA e nella realizzazione di una pipeline in grado di ricavare accurate mappe di disparità in tempo reale acquisendo le immagini da una camera stereo.

Real-time measurement of radiocarpal joint angle during dart-thrower's movement

Recently, a renewed attention has been drawn into the dart-thrower's motion as the radiocarpal joint is unique to humans and this is believed to have played a pivotal role in human evolution. Considering the importance of the motion and the complexity of the wrist joint, there have been many articles discussing the kinematics behind this movement. CT scan techniques have been used in a number of these research activities. Due to limitations in the speed of the image acquisition, the positions of the wrist were recorded in static postures. To our knowledge, a data acquisition for the motion with realtime capturing has not been reported. This paper presents the use of a 3D vision-based motion capture device. Leap Motion Controller (LMC), for measuring the radiocarpal joint angles during the dart-thrower's motion in a real-time analysis. The practical capability of the LMC in measuring dart-thrower's motion was examined in a trial involving four subjects and the angles were compared to the angles acquired from an inertial measurement unit (IMU). The results confirmed the LMC can successfully be used in the application of measuring radiocarpal kinematics" of dart-thrower's motion.

Handheld 3D thermography using range sensing and computer vision

This thesis developed a method for real-time and handheld 3D temperature mapping using a combination of off-the-shelf devices and efficient computer algorithms. It contributes a new sensing and data processing framework to the science of 3D thermography, unlocking its potential for application areas such as building energy auditing and industrial monitoring. New techniques for the precise calibration of multi-sensor configurations were developed, along with several algorithms that ensure both accurate and comprehensive surface temperature estimates can be made for rich 3D models as they are generated by a non-expert user.

Correlating Multiple 2D Vision Trackers for 3D Object Tracking on Construction Sites

Tracking methods have the potential to retrieve the spatial location of project related entities such as personnel and equipment at construction sites, which can facilitate several construction management tasks. Existing tracking methods are mainly based on Radio Frequency (RF) technologies and thus require manual deployment of tags. On construction sites with numerous entities, tags installation, maintenance and decommissioning become an issue since it increases the cost and time needed to implement these tracking methods. To address these limitations, this paper proposes an alternate 3D tracking method based on vision. It operates by tracking the designated object in 2D video frames and correlating the tracking results from multiple pre-calibrated views using epipolar geometry. The methodology presented in this paper has been implemented and tested on videos taken in controlled experimental conditions. Results are compared with the actual 3D positions to validate its performance.