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Wyszukujesz frazę "corner detection" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Fusion of door and corner features for scene recognition
Autorzy:
Chacon-Murguia, M. I.
Sandoval-Rodriguez, R.
Guerrero-Saucedo, C. P.
Powiązania:
https://bibliotekanauki.pl/articles/384964.pdf
Data publikacji:
2011
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
scene recognition
robotics
corner detection
Opis:
Scene recognition is a paramount task for autonomous systems that navigate in open scenarios. In order to achie ve high scene recognition performance it is necesary to use correct information. Therefore, data fusion is beco ming a paramount point in the design of scene recognition systems. This paper presents a scenery recognition system using a neural network hierarchical approach. The system is based on information fusion in indoor scenarios. The system extracts relevant information with respect to color and landmarks. Color information is related mainly to localization of doors. Landmarks are related to corner de tection. The corner detection method proposed in the pa per based on corner detection windows has 99% detection of real corners and 13.43% of false positives. The hierar chical neural systems consist on two levels. The first level is built with one neural network and the second level with two. The hierarchical neural system, based on feed for ward architectures, presents 90% of correct recognition in the first level in training, and 95% in validation. The first ANN in the second level shows 90.90% of correct recogni tion during training, and 87.5% in validation. The second ANN has a performance of 93.75% and 91.66% during training and validation, respectively. The total perfor mance of the systems was 86.6% during training, and 90% in validation.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2011, 5, 1; 68-76
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Key-point Detection based Fast CU Decision for HEVC Intra Encoding
Autorzy:
Xu, Z.
Min, B.
Cheung, R. C. C.
Powiązania:
https://bibliotekanauki.pl/articles/226128.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
HEVC
video coding
fast CU decision
corner detection
Opis:
As the most recent video coding standard, High Efficiency Video Coding (HEVC) adopts various novel techniques, including a quad-tree based coding unit (CU) structure and additional angular modes used for intra encoding. These new techniques achieve a notable improvement in coding efficiency at the penalty of significant computational complexity increase. Thus, a fast HEVC coding algorithm is highly desirable. In this paper, we propose a fast intra CU decision algorithm for HEVC to reduce the coding complexity, mainly based on a key-point detection. A CU block is considered to have multiple gradients and is early split if corner points are detected inside the block. On the other hand, a CU block without corner points is treated to be terminated when its RD cost is also small according to statistics of the previous frames. The proposed fast algorithm achieves over 62% encoding time reduction with 3.66%, 2.82%, and 2.53% BD-Rate loss for Y, U, and V components, averagely. The experimental results show that the proposed method is efficient to fast decide CU size in HEVC intra coding, even though only static parameters are applied to all test sequences.
Źródło:
International Journal of Electronics and Telecommunications; 2018, 64, 3; 321-327
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analysis of operators for detection of corners set in automatic image matching
Autorzy:
Zawieska, D.
Powiązania:
https://bibliotekanauki.pl/articles/129929.pdf
Data publikacji:
2011
Wydawca:
Stowarzyszenie Geodetów Polskich
Tematy:
feature detection
corner detection
3D modelling
image matching
funkcja wykrywania
wykrywanie krawędzi
modelowanie 3D
dopasowanie obrazów
Opis:
Reconstruction of three dimensional models of objects from images has been a long lasting research topic in photogrammetry and computer vision. The demand for 3D models is continuously increasing in such fields as cultural heritage, computer graphics, robotics and many others. The number and types of features of a 3D model are highly dependent on the use of the models, and can be very variable in terms of accuracy and time for their creation. In last years, both computer vision and photogrammetric communities have approached the reconstruction problems by using different methods to solve the same tasks, such as camera calibration, orientation, object reconstruction and modelling. The terminology which is used for addressing the particular task in both disciplines is sometimes diverse. On the other hand, the integration of methods and algorithms coming from them can be used to improve both. The image based modelling of an object has been defined as a complete process that starts with image acquisition and ends with an interactive 3D virtual model. The photogrammetric approach to create 3D models involves the followings steps: image pre-processing, camera calibration, orientation of images network, image scanning for point detection, surface measurement and point triangulation, blunder detection and statistical filtering, mesh generation and texturing, visualization and analysis. Currently there is no single software package available that allows for each of those steps to be executed within the same environment. For high accuracy of 3D objects reconstruction operators are required as a preliminary step in the surface measurement process, to find the features that serve as suitable points when matching across multiple images. Operators are the algorithms which detect the features of interest in an image, such as corners, edges or regions. This paper reports on the first phase of research on the generation of high accuracy 3D model measurement and modelling, focusing upon the application of different operators for accurate feature point extraction. The implementation of those operators is discussed and performance of differen operators is analysed. The optimal operator for high accuracy close range object reconstruction is then highlighted. This research has facilitated a development of the feature extraction and image measurement process that will be central to the development of an automatic procedure for high accuracy point cloud generation in multi image networks where robust orientation and 3D point determination will facilitate surface measurement and modelling within a single software system.
Źródło:
Archiwum Fotogrametrii, Kartografii i Teledetekcji; 2011, 22; 423-436
2083-2214
2391-9477
Pojawia się w:
Archiwum Fotogrametrii, Kartografii i Teledetekcji
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Automatyczna orientacja obrazów cyfrowych na przykładzie wybranej geometrii sieci zdjęć
Automatic orientation of digital images using the example of selected geometry of a network of images
Autorzy:
Zawieska, D.
Powiązania:
https://bibliotekanauki.pl/articles/131129.pdf
Data publikacji:
2012
Wydawca:
Stowarzyszenie Geodetów Polskich
Tematy:
operatory detekcji narożników
dopasowanie zdjęć
modelowanie 3D
operators of corner detection
image matching
3D modelling
Opis:
Celem niniejszego referatu jest przeanalizowanie działania wybranych algorytmów, które automatycznie obliczą elementy orientacji zewnętrznej sieci zdjęć a następnie wyznaczą współrzędne chmury punktów 3D, opisujących model badanego obiektu. Do obliczeń wykorzystano autorski program, realizujący kolejne etapy tworzenia modelu 3D. Pierwsza faza obejmowała wyróżnienie na poszczególnych zdjęciach elementów charakterystycznych, gdzie wykorzystane zostały operatory detekcji narożników SIFT i SUSAN. Następnym krokiem było połączenie punktów homologicznych na sąsiednich zdjęciach. Sposób realizacji tego kroku jest determinowany przez wybór typu operatora. Operator SIFT posiada dedykowany mechanizm tworzenia par, podczas gdy operator SUSAN wymaga utworzenia odrębnych metod. Do dopasowania punktów wykorzystano metodę Area Base Matching, zmodyfikowaną na potrzeby modelowania 3D. Na podstawie tak zebranych danych, kolejnym etapem jest wyznaczenie współrzędnych 3D chmury punktów mierzonego obiektu. W niniejszym referacie przedstawiono dwa rozwiązania. Jedno z nich realizuje dopasowywanie zdjęć parami, korzystając z macierzy podstawowej a drugie trójkami, wykorzystując rachunek tensorowy. W praktyce, pierwsze rozwiązanie wyznaczające punkty modelu okazało się mniej stabilne numerycznie, co może prowadzić do znacznych błędów w modelu końcowym. Drugie rozwiązanie jest trudniejsze do wykorzystania, gdyż wymaga odnalezienia odpowiadających sobie punktów na co najmniej trzech zdjęciach. Eksperymenty przeprowadzono na wybranych obiektach bliskiego zasięgu, z odpowiednio wykonaną geometrią zdjęć, tworzących pierścień (okrąg) wokół mierzonego obiektu.
The objective of this paper is to analyse operations of selected algorithms, which will automatically compute elements of external orientation of a network of photographs and then, they will determine co-ordinates of a 3D cloud of points, which describe a model of the analysed object. The author’s software tool has been utilised for calculations; it performs successive stages of the 3D model generation: detection of characteristic points, point matching on successive photographs, determination of a tensor, calibration and 3D point cloud generation. A series of experiments have been performed in order to evaluate selection of the optimum solution. The first stage included distinguishing of characteristic elements on particular photographs; corner detection operators, SIFT and SUSAN were applied for that stage. The next step concerned connection of homological points on neighbouring photographs. The method of implementation of that step is determined by selection of the operator type. The SIFT operator has the dedicated mechanism of pair creation, whilst the SUSAN operator requires creation of separate methods. The Area Base Matching method, modified according to the demands of 3D modelling, was used for the needs of point matching. This method investigates correlation of the background within the neighbourhood of characteristic points and uses the results of that investigations to match the photographs. Basing on data collected this way, the next stage aims at determination of 3D co-ordinates of the cloud of points of the measured object. Two solutions have been presented in this paper. One of them allows for matching photographs in pairs, using the fundamental matrix; the second solution allows for threesome matching of photographs, using the tensor calculus. In practice, the first solution, which determines the model points, turned to be less numerically stable, what may lead to considerable errors of the final model. The second solution is more difficult to use, since it requires that corresponding points are found in at least three photographs. Experiments were performed for selected close range objects, with the appropriate specified geometry of photographs, which created a ring around the measured object.
Źródło:
Archiwum Fotogrametrii, Kartografii i Teledetekcji; 2012, 23; 509-519
2083-2214
2391-9477
Pojawia się w:
Archiwum Fotogrametrii, Kartografii i Teledetekcji
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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