熱像儀，能感測可見光感測器無法取得的訊息，因此若能透過熱像儀器進行環境偵測，便能得到一般可見光感測器無法獲取的資料。本研究擬以四旋翼UAS酬載熱像儀得到局部區域高解析度之地面熱資訊以便作為地溫研究之背景資料使用。而一般地溫研究區，不易佈設控制點，因此本研究除於無人機上酬載熱像儀之外，並將搭載Trimble BD970 GNSS OEM接收模組，嘗試以少量地面控制點、以及GNSS動態後處理的方式取得取像時對應的GNSS觀測量輔助熱像定位定向。本研究中針對國立政治大學旁的指南溪實驗區與陽明山國家公園的小油坑實驗區，使用AI-RIDER YJ-1000-HC四旋翼UAS分別酬載熱像儀FLIR Tau 640和巨哥XM6，並且同時搭載Trimble BD970 GNSS OEM接收模組、以及GNSS動態後處理的方式取得取像時對應的GNSS觀測量搭配少量地面控制點輔助熱像定位定向，過程中透過三焦張量剔除自動匹配之誤匹配連結點。實驗結果顯示，兩實驗區所產製之DSM於不易變動區域精度經現有資料檢核均在±1m，而指南溪實驗區產製出地面解析度11公分的數值表面模型(Digital Surface Model, DSM)與正射熱像，且正射熱像平面精度達為47公分；小油坑實驗區產製出地面解析度14公分之DSM與正射熱像，正射熱像平面精度則為67公分，雖然DSM和正射熱像精度無法符合一般常規的測量規範，但成果仍然可以證明熱像直接產製DSM以及正射熱像之可行性，兩實驗區最後皆生成數值溫度表面模型(Digital Surface Temparature Model, DSTM)，顯示本研究所提方法之可行性，所生成之成果可供後續地溫研究使用。 / Thermal infrared images show the temperature change of sensed scenes. Therefore, thermal infrared camera can sense some important information that optical digital cameras cannot do for the environment monitoring. In this study, the Quadcopter UAS for thermal image collection applied to geothermal study will be developed. FIIR Tau 640 and Magnity Eletric XM6 thermal infrared sensor will be used in this thermal image collection system separately two test areas, Zhinan River nearby NCCU and Xiaoyoukeng, in the Yangmingshan National Park. Additionally, Trimble BD970 GNSS OEM board will be carried on the Quadcopter UAS to collect dual-frequency GNSS observations for determining the flying trajectory by Post-processed kinematic (PPK) technique to support the positioning and orientating of collected thermal images, and the trifocal tensor will be used to delete wrong matching tie images points. From the tests, the differences between produced DSM and existing DSM data are ± 1 m on uneasy change ground surface in two test areas. The resolution of produced DSM and thermal orthoimages are about 11 cm in Zhinan River, and 14cm in Xiaoyoukeng area. The accuracy of thermal orthoimages is 47cm in Zhinan River and 67cm in Xiaoyoukeng area. The accuracy of thermal orthoimages may not comply with a normal surveying standard, but it proves the possibility of DSM and orthorectifed thermal images generated from thermal images directly. Digital Surface Temparature Model (DSTM) produced in both tests can be used for volcanic geothermal monitoring in the future.

L'imagerie numérique, de la synthèse d'images à la vision par ordinateur est en train de connaître une forte évolution, due entre autres facteurs à la démocratisation et au succès commercial des caméras 3D. Dans le même contexte, l'impression 3D grand public, qui est en train de vivre un essor fulgurant, contribue à la forte demande sur ce type de caméra pour les besoins de la numérisation 3D. L'objectif de cette thèse est d'acquérir et de maîtriser un savoir-faire dans le domaine de la capture/acquisition de modèles 3D en particulier sur l'aspect rendu réaliste. La réalisation d'un scanner 3D à partir d'une caméra RGB-D fait partie de l'objectif. Lors de la phase d'acquisition, en particulier pour un dispositif portable, on est confronté à deux problèmes principaux, le problème lié au référentiel de chaque capture et le rendu final de l'objet reconstruit. / Digital imaging, from the synthesis of images to computer vision isexperiencing a strong evolution, due among other factors to the democratization and commercial success of 3D cameras. In the same context, the consumer 3D printing, which is experiencing a rapid rise, contributes to the strong demand for this type of camera for the needs of 3D scanning. The objective of this thesis is to acquire and master a know-how in the field of the capture / acquisition of 3D models in particular on the rendered aspect. The realization of a 3D scanner from a RGB-D camera is part of the goal. During the acquisition phase, especially for a portable device, there are two main problems, the problem related to the repository of each capture and the final rendering of the reconstructed object.

Cette thèse aborde le problème de la calibration d’un ensemble de capteurscomposé d’une centrale inertielle, d’un magnétomètre et d’une caméra, avecpour objectif leur intégration sur un système très compact : un mini-drone.Cette étude expose tout d’abord les contraintes imposées par l’application surle choix des capteurs et les solutions envisagées notamment pour résoudre leproblème de la synchronisation des mesures. Après avoir étudié les techniquesde calibration existantes, une méthode permettant la calibration de l’ensembledes capteurs (accéléromètre, gyromètre, magnétomètre et caméra) est présentée.La solution proposée permet également d’estimer les changements de repèresentre les différents capteurs. Elle a la particularité de ne nécessiter l’emploid’aucun matériel particulier. D’autre part, l’intégration de ces capteurs dans unsystème aussi compact soulève de nouvelles difficultés. Dans ces conditions, leschamps magnétiques créés par les actionneurs du drone perturbent les mesuresdu magnétomètre se trouvant à proximité. Une nouvelle méthode est proposéeafin d’estimer et de compenser dynamiquement ces perturbations magnétiquesen fonction de l’état des actionneurs du drone. Enfin, deux applications dusystème comprenant une centrale inertielle et une caméra sont présentées :la construction de mosaïques d’images géo-référencées et la stabilisation devidéos. Ces deux applications exploitent les mesures des capteurs inertiels afind’effectuer un traitement en temps réel pour un coût calculatoire très faible. / This thesis deal with the issue of the calibration of a group of sensor composedof an inertial unit, a magnetometer and a camera. It aims at integratingthem into a very compact system : a mini-drone. First of all, this study outlinesthe constraints imposed by the application on the choice of the sensors andthe solutions considered to solve the measures synchronization issue. Afterstudying existing calibration techniques, a method for the calibration of allthe sensors (accelerometer, gyroscope, magnetometer and camera) is presented.The proposed solution allows to estimate the frame transformation between thedifferent sensors. It has the advantage of not requiring the use of any specialequipment. Furthermore, the integration of these sensors into a compact systemraises new difficulties. Under these conditions, the magnetic fields created bythe drone actuators disrupt magnetometer measurements. A new method isproposed to estimate and compensate for these magnetic disturbances. Thecompensation is dynamically adapted based on the state of the drone actuators.Finally, two applications of the system including an inertial unit and a cameraare presented : the construction of geo-referenced images mosaic and videostabilization. Both applications use measurements of inertial sensors and precisecalibration to perform a real-time processing for a very low computational cost.

Ce mémoire s'intéresse à la vision par ordinateur appliquée à des projets d'art technologique. Le sujet traité est la calibration de systèmes de caméras et de projecteurs dans des applications de suivi et de reconstruction 3D en arts visuels et en art performatif. Le mémoire s'articule autour de deux collaborations avec les artistes québécois Daniel Danis et Nicolas Reeves. La géométrie projective et les méthodes de calibration classiques telles que la calibration planaire et la calibration par géométrie épipolaire sont présentées pour introduire les techniques utilisées dans ces deux projets. La collaboration avec Nicolas Reeves consiste à calibrer un système caméra-projecteur sur tête robotisée pour projeter des vidéos en temps réel sur des écrans cubiques mobiles. En plus d'appliquer des méthodes de calibration classiques, nous proposons une nouvelle technique de calibration de la pose d'une caméra sur tête robotisée. Cette technique utilise des plans elliptiques générés par l'observation d'un seul point dans le monde pour déterminer la pose de la caméra par rapport au centre de rotation de la tête robotisée. Le projet avec le metteur en scène Daniel Danis aborde les techniques de calibration de systèmes multi-caméras. Pour son projet de théâtre, nous avons développé un algorithme de calibration d'un réseau de caméras wiimotes. Cette technique basée sur la géométrie épipolaire permet de faire de la reconstruction 3D d'une trajectoire dans un grand volume à un coût minime. Les résultats des techniques de calibration développées sont présentés, de même que leur utilisation dans des contextes réels de performance devant public. / This thesis focuses on computer vision applications for technological art projects. Camera and projector calibration is discussed in the context of tracking applications and 3D reconstruction in visual arts and performance art. The thesis is based on two collaborations with québécois artists Daniel Danis and Nicolas Reeves. Projective geometry and classical camera calibration techniques, such as planar calibration and calibration from epipolar geometry, are detailed to introduce the techniques implemented in both artistic projects. The project realized in collaboration with Nicolas Reeves consists of calibrating a pan-tilt camera-projector system in order to adapt videos to be projected in real time on mobile cubic screens. To fulfil the project, we used classical camera calibration techniques combined with our proposed camera pose calibration technique for pan-tilt systems. This technique uses elliptic planes, generated by the observation of a point in the scene while the camera is panning, to compute the camera pose in relation to the rotation centre of the pan-tilt system. The project developed in collaboration with Daniel Danis is based on multi-camera calibration. For this studio theatre project, we developed a multi-camera calibration algorithm to be used with a wiimote network. The technique based on epipolar geometry allows 3D reconstruction of a trajectory in a large environment at a low cost. The results obtained from the camera calibration techniques implemented are presented alongside their application in real public performance contexts.

Ce mémoire s'inscrit dans le domaine de la vision par ordinateur. Elle s'intéresse à la calibration de systèmes de caméras stéréoscopiques, à la mise en correspondance caméra-projecteur, à la reconstruction 3D, à l'alignement photométrique de projecteurs, au maillage de nuages de points, ainsi qu'au paramétrage de surfaces. Réalisé dans le cadre du projet LightTwist du laboratoire Vision3D, elle vise à permettre la projection sur grandes surfaces arbitraires à l'aide de plusieurs projecteurs. Ce genre de projection est souvent utilisé en arts technologiques, en théâtre et en projection architecturale. Dans ce mémoire, on procède au calibrage des caméras, suivi d'une reconstruction 3D par morceaux basée sur une méthode active de mise en correspondance, la lumière non structurée. Après un alignement et un maillage automatisés, on dispose d'un modèle 3D complet de la surface de projection. Ce mémoire introduit ensuite une nouvelle approche pour le paramétrage de modèles 3D basée sur le calcul efficace de distances géodésiques sur des maillages. L'usager n'a qu'à délimiter manuellement le contour de la zone de projection sur le modèle. Le paramétrage final est calculé en utilisant les distances obtenues pour chaque point du modèle. Jusqu'à maintenant, les méthodes existante ne permettaient pas de paramétrer des modèles ayant plus d'un million de points. / This thesis falls within the field of computer vision. It focuses on stereoscopic camera calibration, camera-projector matching, 3D reconstruction, projector blending, point cloud meshing, and surface parameterization. Conducted as part of the LightTwist project at the Vision3D laboratory, the work presented in this thesis aims to facilitate video projections on large surfaces of arbitrary shape using more than one projector. This type of projection is often seen in theater, digital arts, and architectural projections. To this end, we begin with the calibration of the cameras, followed by a piecewise 3D reconstruction using an active unstructured light scanning method. An automated alignment and meshing of the partial reconstructions yields a complete 3D model of the projection surface. This thesis then introduces a new approach for the parameterization of 3D models based on an efficient computation of geodesic distances across triangular meshes. The only input required from the user is the manual selection of the boudaries of the projection area on the model. The final parameterization is computed using the geodesic distances obtained for each of the model's vertices. Until now, existing methods did not permit the parameterization of models having a million vertices or more.

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The automotive safety company Veoneer are producers of high end driver visual assistance systems, but the knowledge about the absolute accuracy of their dynamic calibration algorithms that estimate the vehicle’s orientation is limited. In this thesis, a novel measurement system is proposed to be used in gathering reference data of a vehicle’s orientation as it is in motion, more specifically the pitch and roll angle of the vehicle. Focus has been to estimate how the uncertainty of the measurement system is affected by errors introduced during its construction, and to evaluate its potential in being a viable tool in gathering reference data for algorithm performance evaluation. The system consisted of three laser distance sensors mounted on the body of the vehicle, and a range of data acquisition sequences with different perturbations were performed by driving along a stretch of road in Linköping with weights loaded in the vehicle. The reference data were compared to camera system data where the bias of the calculated angles were estimated, along with the dynamic behaviour of the camera system algorithms. The experimental results showed that the accuracy of the system exceeded 0.1 degrees for both pitch and roll, but no conclusions about the bias of the algorithms could be drawn as there were systematic errors present in the measurements. / Bilsäkerhetsföretaget Veoneer är utvecklare av avancerade kamerasystem inom förarassistans, men kunskapen om den absoluta noggrannheten i deras dynamiska kalibreringsalgoritmer som skattar fordonets orientering är begränsad. I denna avhandling utvecklas och testas ett nytt mätsystem för att samla in referensdata av ett fordons orientering när det är i rörelse, mer specifikt dess pitchvinkel och rollvinkel. Fokus har legat på att skatta hur osäkerheten i mätsystemet påverkas av fel som introducerats vid dess konstruktion, samt att utreda dess potential när det kommer till att vara ett gångbart alternativ för att samla in referensdata för evaluering av prestandan hos algoritmerna. Systemet bestod av tre laseravståndssensorer monterade på fordonets kaross. En rad mätförsök utfördes med olika störningar introducerade genom att köra längs en vägsträcka i Linköping med vikter lastade i fordonet. Det insamlade referensdatat jämfördes med data från kamerasystemet där bias hos de framräknade vinklarna skattades, samt att de dynamiska egenskaperna kamerasystemets algoritmer utvärderades. Resultaten från mätförsöken visade på att noggrannheten i mätsystemet översteg 0.1 grader för både pitchvinklarna och rollvinklarna, men några slutsatser kring eventuell bias hos algoritmerna kunde ej dras då systematiska fel uppstått i mätresultaten.

This dissertation addresses novel techniques in determining gyroless micro-satellite attitude and attitude rate. The main objective of this thesis is to explore the possibility of using commercially available low cost micro-light star sensor as a stand-alone sensor for micro-satellite attitude as well as attitude rate determination. The objective is achieved by developing accurate and computationally efficient algorithms for the realization of onboard operation of a low fidelity star sensor. All the algorithms developed here are tested with the measurement noise presented in the catalog of the sensor array STAR-1000. A novel accurate second order sliding mode observer (SOSMO) is designed for discrete time uncertain linear multi-output system. Our design procedure is effective for both matched and unmatched bounded uncertain ties and/or disturbances. The bound on uncertainties and/or disturbances is assumed to be unknown. This problem is addressed in this work using the second order multiple sliding modes approach. Second order sliding manifold and corresponding sliding condition for discrete time system is defined similar on the lines of continuous counterpart. Our design is not restricted to a particular class of uncertain (matched) discrete time system. Moreover, it can handle multiple outputs unlike single out-put systems. The observer design is achieved by driving the state observation error and its first order finite difference to the vicinity of the equilibrium point (0,0) in a finite steps and maintaining them in the neighborhood thereafter. The estimation synthesis is based on Quasi Sliding Mode (QSM) design. The problem of designing sliding mode observer for a linear system subjected to unknown inputs requires observer matching condition. This condition is needed to ensure that the state estimation error is a asymptotically stable and is independent of the unknown input during the sliding motion. In the absence of a matching condition, asymptotic stability of the reduced order error dynamics on the sliding surface is not guaranteed. However, unknown bounded inputs guarantee bounded error on state estimation. The QSM design guarantees an ultimate error bound by incorporating Boundary Layer (BL) in its design procedure. The observer achieves one order of magnitude improvement in estimation accuracy than the conventional sliding mode observer (SMO) design for an unknown input. The observer estimation errors, satisfying the given stability conditions, converge to an ultimate finite bound (with in the specified BL) of O(T2), where T Is the sampling period. A relation between sliding mode gain and boundary layer is established for the existence of second order discrete sliding motion. The robustness of the proposed observer with respect to measurement noise is also analyzed. The design algorithm is very simple to apply and is implemented for two examples with different classes of disturbances (matched and unmatched) to show the effectiveness of the design. Simulation results show the robustness with respect to the measurement noise for SOSMO. Second order sliding mode observer gain can be calculated off-line and the same gain can work for large band of disturbance as long as the disturbance acting on the continuous time system is bounded and smooth. The SOSMO is simpler to implement on board compared to the other traditional nonlinear filters like Pseudo-Linear-Kalman-filter(PLKF); Extended Kalman Filter(EKF). Moreover, SMO possesses an automatic adaptation property same as optimal state estimator(like Kalman filter) with respect to the intensity of the measurement noise. The SMO rejects the noisy measurements automatically, in response to the increased noise intensity. The dynamic performance of the observer on the sliding surface can be altered and no knowledge of noise statistics is required. It is shown that the SOSMO performs more accurately than the PLKF in application to micro-satellite angular rate estimation since PLKF is not an optimal filter. A new method for estimation of satellite angular rates through derivative approach is proposed. The method is based on optic flow of star image patterns formed on a star sensor. The satellite angular rates are derived directly from the 2D-coordinates of star images. Our algorithm is computationally efficient and requires less memory allocation compared to the existing vector derivative approaches, where there is also no need for star identification. The angular rates are computed using least square solution method, based on the measurement equation obtained by optic flow of star images. These estimates are then fed into discrete time second order sliding mode observer (SOSMO). The performance of angular rate estimation by SOSMO is compared with the discrete time First order SMO and PLKF. The SOSMO gives the best estimates as compared to the other two schemes in estimating micro-satellite angular rates in all three axes. The improvement in accuracy is one order of magnitude (around1.7984 x 10−5 rad/ sec,8.9987 x 10−6 rad/ sec and1.4222 x 10−5 rad/ sec in three body axes respectively) in terms of standard deviation in steady state estimation error. A new method and algorithm is presented to determine star camera parameters along with satellite attitude with high precision even if these parameters change during long on-orbit operation. Star camera parameters and attitude need to be determined independent of each other as they both can change. An efficient, closed form solution method is developed to estimate star camera parameters (like focal length, principal point offset), lens distortions (like radial distortion) and attitude. The method is based on a two step procedure. In the first step, all parameters (except lens distortion) are estimated using a distortion free camera model. In the second step, lens distortion coefficient is estimated by linear least squares (LS) method. Here the derived camera parameters in first step are used in the camera model that incorporates distortion. However, this method requires identification of observed stars with the catalogue stars. But, on-orbit star identification is difficult as it utilizes the values of camera calibrating parameters that can change in orbit(detector and optical element alignment get change in orbit due to solar pressure or sudden temperature change) from the ground calibrated value. This difficulty is overcome by employing a camera self-calibration technique which only requires four observed stars in three consecutive image frames. Star camera parameters along with lens (radial and decentering) distortion coefficients are determined by camera self calibration technique. Finally Kalman filter is used to refine the estimated data obtained from the LS based method to improve the level of accuracy. We consider the true values of camera parameters as (u0,v0) = (512.75,511.25) pixel, f = 50.5mm; The ground calibrated values of those parameters are (u0,v0) =( 512,512) pixel, f = 50mm; Worst case radial distortion coefficient affecting the star camera lens is considered to be k1 =5 x 10−3 .Our proposed method of attitude determination achieves accuracy of the order of magnitude around 6.2288 x 10−5 rad,3.3712 x 10−5 radand5.8205 x 10−5 rad in attitude angles φ,θ and ψ. Attitude estimation by existing methods in the literature diverges from the true value since they utilize the ground calibrated values of camera parameters instead of true values. To summarize, we developed a formal theory of discrete time Second Order Sliding Mode Observer for uncertain multi-output system. Our methods achieve the desired accuracy while estimating satellite attitude and attitude rate using low fidelity star sensor data. Our methods require lower on-board processing requirement and less memory allocation; thus are suitable for micro-satellite applications. Thus, the objective of using low fidelity star sensor as stand-alone sensor in micro-satellite application is achieved.

Les systèmes multicaméras utilisés pour la vidéosurveillance sont complexes, lourds et coûteux. Pour la surveillance d'une pièce, serait-il possible de les remplacer par un système beaucoup plus simple utilisant une seule caméra et une ou plusieurs sources lumineuses en misant sur les ombres projetées pour obtenir de l'information 3D ? Malgré les résultats intéressants offerts par les systèmes multicaméras, la quantité d'information à traiter et leur complexité limitent grandement leur usage. Dans le même contexte, nous proposons de simplifier ces systèmes en remplaçant une caméra par une source lumineuse. En effet, une source lumineuse peut être vue comme une caméra qui génère une image d'ombre révélant l'objet qui bloque la lumière. Notre système sera composé par une seule caméra et une ou plusieurs sources lumineuses infrarouges (invisibles à l'oeil). Malgré les difficultés prévues quant à l'extraction de l'ombre et la déformation et l'occultation de l'ombre par des obstacles (murs, meubles...), les gains sont multiples en utilisant notre système. En effet, on peut éviter ainsi les problèmes de synchronisation et de calibrage de caméras et réduire le coût en remplaçant des caméras par de simples sources infrarouges. Nous proposons deux approches différentes pour automatiser la reconnaissance de postures humaines. La première approche reconstruit la forme 3D d'une personne pour faire la reconnaissance de la posture en utilisant des descripteurs de forme. La deuxième approche combine directement l'information 2D (ombre+silhouette) pour faire la reconnaissance de postures. Scientifiquement, nous cherchons à prouver que l'information offerte par une silhouette et l'ombre générée par une source lumineuse est suffisante pour permettre la reconnaissance de postures humaines élémentaires (p.ex. debout, assise, couchée, penchée, etc.). Le système proposé peut être utilisé pour la vidéosurveillance d'endroits non encombrés tels qu'un corridor dans une résidence de personnes âgées (pour la détection des chutes p. ex.) ou d'une compagnie (pour la sécurité). Son faible coût permettrait un plus grand usage de la vidéosurveillance au bénéfice de la société. Au niveau scientifique, la démonstration théorique et pratique d'un tel système est originale et offre un grand potentiel pour la vidéosurveillance. / Human posture recognition (HPR) from video sequences is one of the major active research areas of computer vision. It is one step of the global process of human activity recognition (HAR) for behaviors analysis. Many HPR application systems have been developed including video surveillance, human-machine interaction, and the video retrieval. Generally, applications related to HPR can be achieved using mainly two approaches : single camera or multi-cameras. Despite the interesting performance achieved by multi-camera systems, their complexity and the huge information to be processed greatly limit their widespread use for HPR. The main goal of this thesis is to simplify the multi-camera system by replacing a camera by a light source. In fact, a light source can be seen as a virtual camera, which generates a cast shadow image representing the silhouette of the person that blocks the light. Our system will consist of a single camera and one or more infrared light sources. Despite some technical difficulties in cast shadow segmentation and cast shadow deformation because of walls and furniture, different advantages can be achieved by using our system. Indeed, we can avoid the synchronization and calibration problems of multiple cameras, reducing the cost of the system and the amount of processed data by replacing a camera by one light source. We introduce two different approaches in order to automatically recognize human postures. The first approach directly combines the person’s silhouette and cast shadow information, and uses 2D silhouette descriptor in order to extract discriminative features useful for HPR. The second approach is inspired from the shape from silhouette technique to reconstruct the visual hull of the posture using a set of cast shadow silhouettes, and extract informative features through 3D shape descriptor. Using these approaches, our goal is to prove the utility of the combination of person’s silhouette and cast shadow information for recognizing elementary human postures (stand, bend, crouch, fall,...) The proposed system can be used for video surveillance of uncluttered areas such as a corridor in a senior’s residence (for example, for the detection of falls) or in a company (for security). Its low cost may allow greater use of video surveillance for the benefit of society.

This thesis deals with reconstruction of golf ball position using multiple cameras. Reconstruction will be used for golf simulator project. System is using fotogrametric calibration and triangulation algorithm for obtaing point coordinates. Work also discuss options for camera selection. The result is making of prototype of the simulator.