Robust Visual Correspondence: Theory and Applications

Visual correspondence represents one of the most important tasks in computer vision. Given two sets of pixels (i.e. two images), it aims at finding corresponding pixel pairs belonging to the two sets (homologous pixels). As a matter of fact, visual correspondence is commonly employed in fields such as stereo correspondence, change detection, image registration, motion estimation, pattern matching, image vector quantization. The visual correspondence task can be extremely challenging in presence of disturbance factors which typically affect images. A common source of disturbances can be related to photometric distortions between the images under comparison. These can be ascribed to the camera sensors employed in the image acquisition process (due to dynamic variations of camera parameters such as auto-exposure and auto-gain, or to the use of different cameras), or can be induced by external factors such as changes of the amount of light emitted by the sources or viewing of non-lambertian surfaces at different angles. All of these factors tend to produce brightness changes in corresponding pixels of the two images that can not be neglected in real applications implying visual correspondence between images acquired from different spatial points (e.g. stereo vision) and/or different time instants (e.g. pattern matching, change detection). In addition to photometric distortions, differences between corresponding pixels can also be due to the noise introduced by camera sensors. Finally, the acquisition of images from different spatial points or different time instants can also induce occlusions. Evaluation assessments have also been proposed which compared visual correspondence approaches for tasks such as stereo correspondence (Chambon & Crouzil, 2003), image registration (Zitova & Flusser, 2003) and image motion (Giachetti, 2000)

Uma proposta experimental de reconstrução 3D a partir de imagens ortogonais

Advances in the last decade in the field of computer vision have brought great benefits to virtual reality applications, with photogrammetry as a major driver. This technique became popular after the emergence of UAVs, adding improvements to areas such as civil engineering, agronomy, and geoscience, making it possible to map a specific region with aerial missions. In this context, this work presents a proposal to perform 3D reconstruction real scale scenarios overflown by a UAV. For this, an approach in C ++ was developed capable of performing this reconstruction for a set of unordered images. The Struct From Motion methodology was used to perform the calculation of the odometer of the cameras at the time of image capture. Finally, the Multi-View Stereo technique is applied to obtain a dense point cloud of scenery. As innovative methodologies, the GPS coordinates of each image are used to obtain a real scale reconstruction and an adjustment during propagation to improve performance in regions with little color variation. The results obtained were satisfactory, where the reconstruction using aerial images presented a defined result and with measures similar to those found on Google Maps, obtaining a maximum error of 1,59%.Os avanços na última década na área da visão computacional trouxeram grandes benefícios para aplicações de realidade virtual, tendo a fotogrametria como um grande impulsionador. Essa técnica se popularizou após o surgimento dos UAVs, agregando melhorias a áreas como a engenharia civil, agronomia e geociência possibilitando realizar um mapeamento de uma região específica com missões aéreas. Neste contexto, este trabalho apresenta uma proposta de realizar a reconstrução 3D em escala real de cenários sobrevoados por um UAV. Para isso, foi desenvolvida uma abordagem em C++ capaz de realizar essa reconstrução para um conjunto de imagens não ordenadas. A metodologia Struct From Motion foi utilizada para realizar o cálculo da odometria das câmeras no momento da captura da imagem. Por fim, a técnica Multi-View Stereo é aplicada para obtenção de uma nuvem densa de pontos do cenário. Como metodologias inovadoras, tem-se a utilização das coordenadas de GPS de cada imagens para obtenção de uma reconstrução em escala real e um ajuste durante a propagação para melhorar o desempenho em regiões com pouca variação de cor. Os resultados obtidos foram satisfatórios, onde a reconstrução utilizando as imagens aéreas apresentou um resultado definido e com medidas similares as encontradas no Google Maps, obtendo um erro máximo de 1,59%

Cable Tension Monitoring using Non-Contact Vision-based Techniques

In cable-stayed bridges, the structural systems of tensioned cables play a critical role in structural and functional integrity. Thereby, tensile forces in the cables become one of the essential indicators in structural health monitoring (SHM). In this thesis, a video image processing technology integrated with cable dynamic analysis is proposed as a non-contact vision-based measurement technique, which provides a user-friendly, cost-effective, and computationally efficient solution to displacement extraction, frequency identification, and cable tension monitoring. In contrast to conventional contact sensors, the vision-based system is capable of taking remote measurements of cable dynamic response while having flexible sensing capability. Since cable detection is a substantial step in displacement extraction, a comprehensive study on the feasibility of the adopted feature detector is conducted under various testing scenarios. The performance of the feature detector is quantified by developing evaluation parameters. Enhancement methods for the feature detector in cable detection are investigated as well under complex testing environments. Threshold-dependent image matching approaches, which optimize the functionality of the feature-based video image processing technology, is proposed for noise-free and noisy background scenarios. The vision-based system is validated through experimental studies of free vibration tests on a single undamped cable in laboratory settings. The maximum percentage difference of the identified cable fundamental frequency is found to be 0.74% compared with accelerometer readings, while the maximum percentage difference of the estimated cable tensile force is 4.64% compared to direct measurement by a load cell

RELIABLE REJECTION OF MISMATCHING CANDIDATES FOR EFFICIENT ZNCC TEMPLATE MATCHING

This paper presents a method that reduces the computational cost of template matching based on the Zero-mean Normalized Cross-Correlation (ZNCC) without compromising the accuracy of the results. A very effective condition is determined at a small and �xed cost that allow to rapidly detect a large number of mismatching candidates with no need to compute the ZNCC score. Then, thanks to the use of an additional set of conditions, the computation of the whole ZNCC function is typically required only for a very small number of candidates. Experimental results demonstrate the effectiveness of our approach. Index Terms — Template matching, ZNCC, cross correlation, fast, exhaustiv