Robust Motion Detection in Real-Life Scenarios (SpringerBriefs in Computer Science) - Softcover
Buch 36 von 322: SpringerBriefs in Computer Science
Inhaltsangabe
This work proposes a complete sensor-independent visual system that provides robust target motion detection. First, the way sensors obtain images, in terms of resolution distribution and pixel neighbourhood, is studied. This allows a spatial analysis of motion to be carried out. Then, a novel background maintenance approach for robust target motion detection is implemented. Two different situations are considered: a fixed camera observing a constant background where objects are moving; and a still camera observing objects in movement within a dynamic background. This distinction lies on developing a surveillance mechanism without the constraint of observing a scene free of foreground elements for several seconds when a reliable initial background model is obtained, as that situation cannot be guaranteed when a robotic system works in an unknown environment. Other problems are also addressed to successfully deal with changes in illumination, and the distinction between foreground and background elements.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Von der hinteren Coverseite
Our knowledge of the surrounding world is obtained by our senses, of which vision is the most important for the information it can provide. In artificial systems, the field of Computer Vision aims to identify physical objects and scenes from captured images, to make useful decisions. This involves the processing and analysis of images, video data, and multi-dimensional data like medical scans.
In this context, motion provides a stimulus for detecting objects in movement within the observed scene. Moreover, motion allows other characteristics to be obtained, such as object shape, speed or trajectory, which are meaningful for detection and recognition. However, the motion observable in a visual input can be due to different factors: movement of the imaged objects, movement of the observer, motion of the light sources, or a combination of these.
This work focuses on motion detection from images captured by perspective and fisheye still cameras, proposing a complete sensor-independent visual system that provides robust target motion detection. First, the way sensors obtain images is studied, allowing a spatial analysis of motion to be carried out. Then, a novel background maintenance approach for robust target motion detection is implemented. Two different situations are considered: a fixed camera observing a constant background where objects are moving; and a still camera observing objects in movement against a dynamic background. This permits the development of a surveillance mechanism that removes the constraint of observing a scene free of foreground elements to obtain a reliable background model, since this situation cannot be guaranteed when operating in an unknown environment. Other problems are also addressed for the successful handling of changes in illumination, the distinction between foreground and background elements, and non-uniform vacillating backgrounds.„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Weitere beliebte Ausgaben desselben Titels
Suchergebnisse für Robust Motion Detection in Real-Life Scenarios (SpringerBrie...
Beispielbild für diese ISBN
Robust Motion Detection in Real-life Scenarios
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Verkäuferbewertung 5 von 5 Sternen
Paperback. Zustand: Brand New. 2012 edition. 120 pages. 9.00x6.00x0.50 inches. In Stock. Artikel-Nr. x-1447142152
Neu kaufen
EUR 76,02
EUR 11,56 Versand
Versand von Vereinigtes Königreich nach USA
Versand von Vereinigtes Königreich nach USA
Anzahl: 2 verfügbar
Foto des Verkäufers
Robust Motion Detection in Real-Life Scenarios
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Our knowledge of the surrounding world is obtained by our senses of perception. Among them, vision is undoubtedly the most important for the information it can provide. In artificial systems, this discipline, known as Computer Vision, mainly tries to identify physical objects and scenes from captured images to be able to make useful decisions. For that, the processing and analysis of images, video sequences, views from multiple cameras, or multi-dimensional data like a medical scanner, are carried out.In this context, motion plays a main role since it provides a stimulus for detecting objects in movement within the observed scene. Moreover, motion allows other characteristics to be obtained such as, for instance, object shape, speed or trajectory, which are meaningful for detection and recognition. Nevertheless, the motion observable in a visual input could be due to different factors: movement of the imaged objects (targets and/or vacillating background elements), movement of the observer, motion of the light sources or a combination of (some of) them. Therefore, image analysis for motion detection will be conditional upon the considered factors. In particular, in this work, there is a focus on motion detection from images captured by perspective and fisheye still cameras. As cameras are still, ego-motion is not considered, although all the other factors can occur at any time.With that assumption, the work proposes a complete sensor-independent visual system which provides robust target motion detection. So, firstly, the way sensors obtain images of the world, in terms of resolution distribution and pixel neighbourhood, is studied. In that way, a proper spatial analysis of motion can be carried out. Then, a novel background maintenance approach for robust target motion detection is implemented. On this matter, two different situations are considered: (1) a fixed camera observing a constant background where interest objects are moving; and, (2) a still camera observing interest objects in movement within a dynamic background. The reason for this distinction lies on developing, from the first analysis, a surveillance mechanism which removes the constraint of observing a scene free of foreground elements during several seconds when a reliable initial background model is obtained, since that situation cannot be guaranteed when a robotic system works in an unknown environment. Furthermore, on the way to achieve an ideal background maintenance system, other canonical problems are addressed such that the proposed approach successfully deals with (gradual and global) changes in illumination, the distinction between foreground and background elements in terms of motion and motionless, and non-uniform vacillating backgrounds.In this context, motion plays a main role since it provides a stimulus for detecting objects in movement within the observed scene. Moreover, motion allows other characteristics to be obtained such as, for instance, object shape, speed or trajectory, which are meaningful for detection and recognition. Nevertheless, the motion observable in a visual input could be due to different factors: movement of the imaged objects (targets and/or vacillating background elements), movement of the observer, motion of the light sources or a combination of (some of) them. Therefore, image analysis for motion detection will be conditional upon the considered factors. In particular, in this work, there is a focus on motion detection from images captured by perspective and fisheye still cameras. As cameras are still, ego-motion is not considered, although all the other factors can occur at any time.With that assumption, the work proposes a complete sensor-independent visual system which provides robust target motion detection. So, firstly, the way sensors obtain images of the world, in terms of resolution distribution and pixel neighbourhood, is studied. In that way, a proper spati. Artikel-Nr. 9781447142157
Neu kaufen
EUR 58,39
EUR 60,98 Versand
Versand von Deutschland nach USA
Versand von Deutschland nach USA
Anzahl: 1 verfügbar
Foto des Verkäufers
Robust Motion Detection in Real-Life Scenarios
Anbieter: preigu, Osnabrück, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Robust Motion Detection in Real-Life Scenarios | Ester Martínez-Martín (u. a.) | Taschenbuch | SpringerBriefs in Computer Science | xii | Englisch | 2012 | Springer | EAN 9781447142157 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Artikel-Nr. 106498497
Neu kaufen
EUR 50,35
EUR 70,00 Versand
Versand von Deutschland nach USA
Versand von Deutschland nach USA
Anzahl: 5 verfügbar
Beispielbild für diese ISBN
Robust Motion Detection in Real-Life Scenarios
Anbieter: Buchpark, Trebbin, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This work proposes a complete sensor-independent visual system that provides robust target motion detection. First, the way sensors obtain images, in terms of resolution distribution and pixel neighbourhood, is studied. This allows a spatial analysis of motion to be carried out. Then, a novel background maintenance approach for robust target motion detection is implemented. Two different situations are considered: a fixed camera observing a constant background where objects are moving; and a still camera observing objects in movement within a dynamic background. This distinction lies on developing a surveillance mechanism without the constraint of observing a scene free of foreground elements for several seconds when a reliable initial background model is obtained, as that situation cannot be guaranteed when a robotic system works in an unknown environment. Other problems are also addressed to successfully deal with changes in illumination, and the distinction between foreground and background elements. Artikel-Nr. 12335364/12
Gebraucht kaufen
EUR 40,86
EUR 105,00 Versand
Versand von Deutschland nach USA
Versand von Deutschland nach USA
Anzahl: 1 verfügbar