Documentation of cultural heritage by means of photogrammetric methods and transfer to GIS

Tarihi eser veya alanları koruma; bu eser veya alanlara ait ilk teknik dokümanları üretmeyi ve bu dokümanları oluşturabilmek için gerekli plan ve çalışmaları organize edebilmeyi gerekli kılar. Elde edilen bu dokümanlar yardımıyla tarihi eser veya alanlarda yapılacak herhangi bir çalışma için istenilen her türlü bilgiye  kolaylıkla ulaşabilmek olanaklı olacaktır. Dijital fotogrametri ve Coğrafi Bilgi Sistemlerinin  (CBS) birlikte kullanılması ile oluşturulacak bir bilgi sistemi, tarihi eser veya alanların korunması konusunda çalışan ve ilgilenen tüm kişilerin ulaşabilecekleri bir ortam sağlayacaktır. Bu çalışmada, tüm bu gelişmelerden yararlanılarak tarihi eserlerin fotogrametrik olarak belgelenmesi ve bu belgelemenin CBS ile en uygun kullanım olanaklarına ulaştırılması amaçlanmıştır. Anahtar Kelimeler: Coğrafi Bilgi Sistemleri, fotogrametri, tarihi eser.Turkey is one of the rare countries with a rich cultural heritage. We have been left with a historic heritage covering the centuries from pre-historic to modern times, which have left the marks of their civilizations on the lands of Anatolia.. Therefore these riches should be preserved and left to the next generations with the care such treasures deserve. We have to be aware of the responsibility of leaving these treasures to the next generations as well as displaying them to the tourists. The saving methods of these treasures are supported by modern technology. Using these methods enables us to increase the efficiency and impact of the saving process. Using the advanced technologies in the disciplines other than architecture and by cooperation among the different fields, the future of cultural heritage can be guaranteed in order to save the historical objects and areas. It is necessary to organize the plans and works covering the necessary technical documents of the objects and lands to preserve these objects and lands. The information system generated by the use of digital photogrammetry and Geographical Information System together will enable any person interested in saving the cultural heritage to reach the necessary data. The aim of this study is to use this technology for the photogrammetric documentation of the cultural heritage and to enable the use of the documentation by using GIS. Keywords: Geographic Information Systems, photogrammetry, cultural heritage

3D Object Recognition with Keypoint Based Algorithms

Object recognition is important in many practical applications of computer vision. Traditional 2D methods are negatively affected by illumination, shadowing and viewpoint. 3D methods have the potential to solve these problems, because 3D models include geometric properties of the objects. In this paper, 3D local feature based algorithms were used for 3D object recognition. The local feature was keypoint. This study aimed to research facilities of keypoints for 3D object recognition. Keypoint is feature of object that is detected by detector algorithms according to certain mathematical base. A recognition system was designed. For this purpose, a database that includes 3D model of objects was created. The algorithms were improved in MATLAB. The keypoints on the 3D models were detected using keypoint detectors. These keypoints were described by keypoints descriptors. The descriptor algorithms detect geometrical relation between each point of point cloud and create a histogram. In the third step, the keypoints in different point clouds are matched using the feature histograms obtained. Statistical methods are used to compare generated histograms. Thus, the two closest similar points between the different point clouds are matched. It is expected that the models with the most corresponding points belong to the same object. Euclidean distance between corresponding keypoints in the two point cloud is calculated. It has been accepted that the points are shorter than 10 mm. The positional accuracy of the matched points has been examined. Iterative Closest Point (ICP) was applied to the matching point clouds for this purpose. As a result, the graphics were generated that showed correct matching ratio and root mean square error. As a result, there are different approaches about 3D object recognition in literature. This study aimed to compare different keypoint detector and descriptor algorithms. Intrinsic Shape Signature (ISS) is keypoint detector algorithms. Point Feature Histograms (PFH) and Fast Point Feature Histograms (FPFH) are keypoint descriptor algorithms. The results of this study will provide guidance for future studies

Documentation And Analysis Of Cultural Heritage By Photogrammetric Methods And Gis

Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2003Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2003Türkiye, geçmişten günümüze uzanan birçok tarihi esere sahip az sayıdaki ülkelerden biridir. Tarih öncesi çağlardan günümüze kadar uzanan, Anadolu toprakları üzerinde zengin uygarlık izleri bırakan, değişik kültürlerden kalan birçok eser, tarihi miras olarak bırakılmıştır. Bu nedenle, miras olarak devraldığımız kültür varlıkları, gelecek kuşaklara da sağlıklı biçimde ulaştırılması gereken bir hazinedir. Bizden öncekilerden devraldığımız bu mirası, sanat ve kültür objeleri olarak, yerli ve yabancı ziyaretçilere sunacağımız gibi, gelecek kuşaklara da sağlıklı ve sağlam biçimde devretme bilinci ve sorumluluğunu taşımak gerekmektedir. Korumaya ait girişimler günümüzdeki mevcut teknolojik araçlar vasıtasıyla desteklenmektedir. Bu araçların kullanılmasıyla şimdiye kadar mümkün olmayan çözümler bulunarak kültürel mirasın korunması daha kolay ve etkin bir şekilde yapılabilmektedir. Mimariden başka disiplinlerden gelen geliştirilmiş teknolojik medyanın kullanımıyla ve farklı disiplinlerde meslek sahipleri arasındaki işbirliği düşünüldüğünde, gelecek nesiller için kültürel mirasın iletimi garanti altına alınabilecektir. Tarihi eser veya alanları koruma; bu eser veya alanlara ait ilk teknik dokümanları üretmeyi ve bu dokümanları oluşturabilmek için gerekli plan ve çalışmaları organize edebilmeyi gerekli kılar. Elde edilen bu dokümanlar yardımıyla tarihi eser veya alanlarda yapılacak herhangi bir çalışma için istenilen her türlü bilgiye kolaylıkla ulaşabilmek olanaklı olacaktır. Digital fotogrametri ve Coğrafi Bilgi Sistemlerinin birlikte kullanılması ile oluşturulacak bir bilgi sistemi, tarihi eser veya alanların korunması konusunda çalışan ve ilgilenen tüm kişilerin ulaşabilecekleri bir ortam sağlayacaktır. Yukarıda da bahsedildiği üzere fotogrametri ve CBS’nin entegrasyonu sonucunda verinin uygun koşullarda ve amaç doğrultusunda kullanılması, analiz edilmesi ve sunulması kültürel mirası koruma çalışmalarında vazgeçilmez bir olanak oluşturmaktadır. Bu çalışmada, tüm bu gelişmelerden yararlanılarak tarihi eserlerin fotogrametrik olarak belgelenmesi ve bu belgelemenin CBS ile en uygun kullanım olanaklarına ulaştırılması amaçlanmıştır.Turkey is one of the rare countries with a rich cultural heritage. We have been left with a historic heritage covering the centuries from pre-historic to modern times, which have left the marks of their civilizations on the lands of Anatolia.. Therefore these riches should be preserved and left to the next generations with the care such treasures deserve. We have to be aware of the responsibility of leaving these treasures to the next generations as well as displaying them to the tourists. The saving methods of these treasures are supported by modern technology. Using these methods enables us to increase the efficiency and impact of the saving process. Using the advanced technologies in the disciplines other than architecture and by cooperation among the different fields, the future of cultural heritage can be guaranteed in order to save the historical objects and areas. It is necessary to organize the plans and works covering the necessary technical documents of the objects and lands to preserve these objects and lands. With the help of these documents, it will be possible to reach the desired information for the works carried on these objects and lands. The information system generated by the use of digital photogrammetry and Geographical Information System together will enable any person interested in saving the cultural heritage to reach the necessary data. As mentioned above, integration of photogrammetry and GIS leads to the efficient use of data, analysis and presentation opportunities, which are very important for saving the cultural heritage. The aim of this study is to use this technology for the photogrammetric documentation of the cultural heritage and to enable the use of the documentation by using GIS.DoktoraPh

Selection of Relevant Geometric Features Using Filter-Based Algorithms for Point Cloud Semantic Segmentation

Semantic segmentation of mobile LiDAR point clouds is an essential task in many fields such as road network management, mapping, urban planning, and 3D High Definition (HD) city maps for autonomous vehicles. This study presents an approach to improve the evaluation metrics of deep-learning-based point cloud semantic segmentation using 3D geometric features and filter-based feature selection. Information gain (IG), Chi-square (Chi2), and ReliefF algorithms are used to select relevant features. RandLA-Net and Superpoint Grapgh (SPG), the current and effective deep learning networks, were preferred for applying semantic segmentation. RandLA-Net and SPG were fed by adding geometric features in addition to 3D coordinates (x, y, z) directly without any change in the structure of the point clouds. Experiments were carried out on three challenging mobile LiDAR datasets: Toronto3D, SZTAKI-CityMLS, and Paris. As a result of the study, it was demonstrated that the selection of relevant features improved accuracy in all datasets. For RandLA-Net, mean Intersection-over-Union (mIoU) was 70.1% with the features selected with Chi2 in the Toronto3D dataset, 84.1% mIoU was obtained with the features selected with the IG in the SZTAKI-CityMLS dataset, and 55.2% mIoU with the features selected with the IG and ReliefF in the Paris dataset. For SPG, 69.8% mIoU was obtained with Chi2 in the Toronto3D dataset, 77.5% mIoU was obtained with IG in SZTAKI-CityMLS, and 59.0% mIoU was obtained with IG and ReliefF in Paris

Classification of Photogrammetric and Airborne LiDAR Point Clouds Using Machine Learning Algorithms

With the development of photogrammetry technologies, point clouds have found a wide range of use in academic and commercial areas. This situation has made it essential to extract information from point clouds. In particular, artificial intelligence applications have been used to extract information from point clouds to complex structures. Point cloud classification is also one of the leading areas where these applications are used. In this study, the classification of point clouds obtained by aerial photogrammetry and Light Detection and Ranging (LiDAR) technology belonging to the same region is performed by using machine learning. For this purpose, nine popular machine learning methods have been used. Geometric features obtained from point clouds were used for the feature spaces created for classification. Color information is also added to these in the photogrammetric point cloud. According to the LiDAR point cloud results, the highest overall accuracies were obtained as 0.96 with the Multilayer Perceptron (MLP) method. The lowest overall accuracies were obtained as 0.50 with the AdaBoost method. The method with the highest overall accuracy was achieved with the MLP (0.90) method. The lowest overall accuracy method is the GNB method with 0.25 overall accuracy

Classification of Photogrammetric and Airborne LiDAR Point Clouds Using Machine Learning Algorithms

With the development of photogrammetry technologies, point clouds have found a wide range of use in academic and commercial areas. This situation has made it essential to extract information from point clouds. In particular, artificial intelligence applications have been used to extract information from point clouds to complex structures. Point cloud classification is also one of the leading areas where these applications are used. In this study, the classification of point clouds obtained by aerial photogrammetry and Light Detection and Ranging (LiDAR) technology belonging to the same region is performed by using machine learning. For this purpose, nine popular machine learning methods have been used. Geometric features obtained from point clouds were used for the feature spaces created for classification. Color information is also added to these in the photogrammetric point cloud. According to the LiDAR point cloud results, the highest overall accuracies were obtained as 0.96 with the Multilayer Perceptron (MLP) method. The lowest overall accuracies were obtained as 0.50 with the AdaBoost method. The method with the highest overall accuracy was achieved with the MLP (0.90) method. The lowest overall accuracy method is the GNB method with 0.25 overall accuracy

Scour patterns around isolated vegetation elements

The complex multi-directional interactions between hydrological, biological and fluvial processes govern the formation and evolution of river landscapes. In this context, as key geomorphological agents, riparian trees are particularly important in trapping sediment and constructing distinct landforms, which subsequently evolve to larger ones. The primary objective of this paper is to experimentally investigate the scour/deposition patterns around different forms of individual vegetation elements. Flume experiments were conducted in which the scour patterns around different representative forms of individual in-stream obstructions (solid cylinder, hexagonal array of circular cylinders, several forms of emergent and submerged vegetation) were monitored by means of a high-resolution laser scanner. The three dimensional scour geometry around the simulated vegetation elements was quantified and discussed based on the introduced dimensionless morphometric characteristics. The findings reveal that the intact vegetation forms generated two elongated scour holes at the downstream with a pronounced ridge. For the impermeable form of the plant, the scour got localized, more deposition was detected within the monitoring zone, and the distance between the obstruction and deposition zone became shorter. It is also shown that with the effect of bending and the subsequent decrease of the projected area of the plant and the increase of bulk volume, the characteristic scour values decrease compared to the intact version, and the scour zone obtains a more elongated form and expands in the downstream direction