Erscheinungsdatum: 15.12.2010, Medium: Taschenbuch, Einband: Kartoniert / Broschiert, Titel: Deformable Surface 3D Reconstruction from Monocular Images, Autor: Salzmann, Mathieu // Salzmann, Matthieu // Fua, Pascal, Verlag: Morgan & Claypool Publishers, Sprache: Englisch, Schlagworte: COMPUTERS // Computer Graphics, Rubrik: Informatik, Seiten: 114, Informationen: Paperback, Gewicht: 230 gr, Verkäufer: averdo
Erscheinungsdatum: 01.12.2010, Medium: Taschenbuch, Einband: Kartoniert / Broschiert, Titel: Deformable Surface 3D Reconstruction from Monocular Images, Autor: Salzmann¿¿, Mathieu // Fua, Pascal, Verlag: Morgan & Claypool Publishers, Sprache: Englisch, Schlagworte: COMPUTERS // Computer Vision & Pattern Recognition // Maschinelles Sehen // Bildverstehen, Rubrik: Informatik, Seiten: 114, Informationen: Paperback, Gewicht: 335 gr, Verkäufer: averdo
Variation Based Dense 3D Reconstruction ab 58.99 € als pdf eBook: Application on Monocular Mini-Laparoscopic Sequences. Aus dem Bereich: eBooks, Sachthemen & Ratgeber, Computer & Internet,
Variation Based Dense 3D Reconstruction ab 59.99 € als Taschenbuch: Application on Monocular Mini-Laparoscopic Sequences. 1st ed. 2016. Aus dem Bereich: Bücher, Ratgeber, Computer & Internet,
Robust Methods for Dense Monocular Non-Rigid 3D Reconstruction and Alignment of Point Clouds ab 79.99 € als pdf eBook: . Aus dem Bereich: eBooks, Sachthemen & Ratgeber, Computer & Internet,
Robust Methods for Dense Monocular Non-Rigid 3D Reconstruction and Alignment of Point Clouds ab 79.99 € als Taschenbuch: 1st ed. 2020. Aus dem Bereich: Bücher, Ratgeber, Computer & Internet,
Simultaneous Localization and Mapping, comprising estimation of robot ego-motion and building a map of the surrounding environment, is one of the most fundamental tasks of mobile robotics. Many SLAM systems proposed in the past make use of the Global Positioning System (GPS), which renders them both expensive and overly dependent on the presence of the GPS signal. We propose an alternative, low-cost approach for portable SLAM which is based on monocular vision, a promising technique due to its flexibility, ease of use, and ease of calibration. In order to perform this task we use an Extended Kalman Filter, one of the most efficient and robust methods used in SLAM systems. We show how it is possible to improve the estimated position and reduce its uncertainty by fusing data from different sensors, in particular using a simple 3-axis accelerometer. We prove, through careful and intelligent selection and tuning of image analysis algorithms, that real-time, low-cost SLAM is feasible. This work is useful to professionals developing SLAM systems and to people in the larger field of computer vision, especially those interested in feature detection and tracking.
Vision based inference for mobile robots in order to avoid obstacles, is one of the most attracted areas for both domains of Computer Vision and Robotics. Computer Vision, more specifically the vision for intelligent machines enables mobile robots to perceive the external world with 'wisdom'. Therefore Vision based obstacle avoidance has become one of the major research areas of Robotics. Estimating the motion path and predicting the motion behavior of a dynamic object with only single camera (monocular vision) is a real challenge. We realized this can be done by analyzing a sequence of image frames extracted from a live video stream. But, these analytic techniques must be extremely fast in real time processing, since the decision drawn within reasonably short response time is the only 'god' to safeguard the robot & ensure the safety of others in environment! Therefore, we postulate a fuzzy-mathematical model: an Artificial Intelligence approach to achieve the ultimate objective, which has a significant impact in terms of simplicity (reduced complexity) together with efficiency (minimized computational overhead: resource consumption), rather than conventional mathematical modeling.
Many applications of video technology require multi-target tracking, for example for indoor or outdoor surveillance, intelligent vehicles, robotics, or experiments in biology. This book shows how specifica of targets influence the design of tracking methods. Four totally different types of targets are tracked, namely fruit flies (drosophila melanogaster), vehicles, pedestrians, and lane marks. The book presents methods for tracking of such targets under various recording settings (i.e. static, or moving cameras, monocular, binocular, or trinocular). In order to further improve the tracking performance, more specific methods are proposed and discussed for the different targets. This book starts with a comprehensive review of state-of-the-art multi-traget tracking methods. It is suitable for students or researchers who would like to have advise about tracking methods possibly applicable to their application, or who are contributing in the computer vision field to the design of tracking methods.