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    Wyświetlanie 1-3 z 3
    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
      Wyświetlanie 1-3 z 3

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