2 research outputs found

    Developing Advanced Photogrammetric Methods for Automated Rockfall Monitoring

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    [eng] In recent years, photogrammetric models have become a widely used tool in the field of geosciences thanks to their ability to reproduce natural surfaces. As an alternative to other systems such as LiDAR (Light Detection and Ranging), photogrammetry makes it possible to obtain 3D points clouds at a lower cost and with a lower learning curve. This combination has allowed the democratisation of this 3D model creation strategy. On the other hand, rockfalls are one of the geological phenomena that represent a risk for society. It is the most common natural phenomenon in mountainous areas and, given its great speed, its hazard is very high. This doctoral thesis deals with the creation of photogrammetric systems and processing algorithms for the automatic monitoring of rockfalls. To this end, 3 fixed camera photogrammetric systems were designed and installed in 2 study areas. In addition, 3 different workflows have been developed, two of which are aimed at obtaining comparisons of higher quality using photogrammetric models and the other focused on automating the entire monitoring process with the aim of obtaining automatic monitoring systems of low temporal frequency. The photogrammetric RasPi system has been designed and installed in the study area of Puigcerc贸s (Catalonia). This very low-cost system has been designed using Raspberry cameras. Despite being a very low-cost and low-resolution system, the results obtained demonstrate its ability to identify rockfalls and pre-failure deformation. The HRCam photogrammetric system has also been designed and installed in the Puigcerc贸s study area. This system uses commercial cameras and more complex control systems. With this system, higher quality models have been obtained that enable better monitoring of rockfalls. Finally, the DSLR system has been designed similarly to the HRCam system but has been installed in a real risk area in the Tajo de San Pedro in the Alhambra (Andalusia). This system has been used to constantly monitor the rockfalls affecting this escarpment. In order to obtain 3D comparisons with the highest possible quality, two workflows have been developed. The first, called PCStacking, consists of stacking 3D models in order to calculate the median of the Z coordinates of each point to generate a new averaged point cloud. This thesis shows the application of the algorithm both with ad hoc created synthetic point clouds and with real point clouds. In both cases, the 25th and 75th percentile errors of the 3D comparisons were reduced from 3.2 cm to 1.4 cm in synthetic tests and from 1.5 cm to 0.5 cm in real conditions. The second workflow that has been developed is called MEMI (Multi-Epoch and Multi-Imagery). This workflow is capable of obtaining photogrammetric comparisons with a higher quality than those obtained with the classical workflow. The redundant use of images from the two periods to be compared reduces the error to a factor of 2 compared to the classical approach, yielding a standard deviation of the comparison of 3D models of 1.5 cm. Finally, the last workflow presented in this thesis is an update and an automation of the method for detecting rockfalls from point-clouds carried out by the RISKNAT research group. The update has been carried out with two objectives in mind. The first is to transfer the entire working method to free licence (both language and programming), and the second is to include in the processing the new algorithms and improvements that have recently been developed. The automation of the method has been performed to cope with the large amount of data generated by photogrammetric systems. It consists of automating all the processes, which means that everything from the capture of the image in the field to the obtention of the rockfalls is performed automatically. This automation poses important challenges, which, although not completely solved, are addressed in this thesis. Thanks to the creation of photogrammetric systems, 3D model improvement algorithms and automation of the rockfall identification workflow, this doctoral thesis presents a solid and innovative proposal in the field of low-cost automatic monitoring. The creation of these systems and algorithms constitutes a further step in the unimpeded expansion of monitoring and warning systems, whose ultimate goal is to enable us to live in a safer world and to build more resilient societies to deal with geological hazards.[cat] En els darrers anys, els models fotogram猫trics s鈥檋an convertit en una eina molt utilitzada en l鈥櫭爉bit de les geoci猫ncies gr脿cies a la seva capacitat per reproduir superf铆cies naturals. Com a alternativa a altres sistemes com el LiDAR (Light Detection and Ranging), la fotogrametria permet obtenir n煤vols de punts 3D a un cost m茅s baix i amb una corba d鈥檃prenentatge menor. Per altra banda, els despreniments de roca s贸n un dels fen貌mens geol貌gics que representen un risc per al conjunt de la societat. Aquesta tesi doctoral aborda la creaci贸 de sistemes fotogram猫trics i algoritmes de processat per al monitoratge autom脿tic de despreniments de roca. Per una banda, s鈥檋a dissenyat un sistema fotogram猫tric de molt baix cost fent servir c脿meres Raspberry Pi, anomenat RasPi System, instal路lat a la zona d鈥檈studi de Puigcerc贸s (Catalunya). Per altra banda, s鈥檋a dissenyat un sistema fotogram猫tric d鈥檃lta resoluci贸 anomenat HRCam tamb茅 instal路lat a la zona d鈥檈studi de Puigcerc贸s. Finalment, s鈥檋a dissenyat un tercer sistema fotogram猫tric de manera similar al sistema HRCam anomenat DSLR, instal路lat en una zona de risc real al Tajo de San Pedro de l鈥橝lhambra (Andalusia). Per obtenir comparacions 3D amb la m脿xima qualitat possible, s鈥檋an desenvolupat dos fluxos de treball. El primer, anomenat PCStacking consisteix a realitzar un apilament de models 3D per tal de calcular la mediana de les coordenades Z de cada punt. El segon flux de treball que s鈥檋a desenvolupat s鈥檃nomena MEMI (Multi-Epoch and Multi-Imagery). Aquest flux de treball 茅s capa莽 d鈥檕btenir comparacions fotogram猫triques amb una qualitat superior a les que s鈥檕btenen amb el flux de treball cl脿ssic. Finalment, el darrer flux de treball que es presenta en aquesta tesi 茅s una actualitzaci贸 i una automatitzaci贸 del m猫tode de detecci贸 de despreniments de roca del grup de recerca RISKNAT. L鈥檃ctualitzaci贸 s鈥檋a dut a terme perseguint dos objectius. El primer, traspassar tot el m猫tode de treball a llic猫ncia lliure (tant llenguatge com programari) i el segon, incloure els nous algoritmes i millores desenvolupats en aquesta tesi en el processat fotogram猫tric Gr脿cies a la creaci贸 dels sistemes fotogram猫trics, algoritmes de millora de models 3D i l鈥檃utomatitzaci贸 en la identificaci贸 de despreniments aquesta tesi doctoral presenta una proposta s貌lida i innovadora en el camp del monitoratge autom脿tic de baix cost. La creaci贸 d鈥檃quests sistemes i algoritmes representen un aven莽 important en l鈥檈xpansi贸 dels sistemes de monitoratge i alerta que tenen com a objectiu final permetre'ns viure en un m贸n m茅s segur i construir societats m茅s resilients enfront dels riscos geol貌gics

    Low cost rototranslational video stabilization algorithm

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    To avoid grabbing the unintentional user motion in a video sequence, video stabilization techniques are used to obtain better-looking video for the final user. We present a low power rototranslational solution, extending our previous work specifically addressed for translational motion only. The proposed technique achieves a high degree of robustness with respect to common difficult conditions like noise perturbations, illumination changes, and motion blurring. Moreover, it is also able to cope with regular patterns, moving objects and it is very precise, reaching about 7% of improvement in jitter attenuation, compared to previous results. Overall performances are competitive also in terms of computational cost: it runs at more than 30 frames /s with VGA sequences, with a CPU ARM926EJ-S at just 100 MHz clock frequency
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