Efficient 3D Scene Modeling and Mosaicing

This book proposes a complete pipeline for monocular (single camera) based 3D mapping of terrestrial and underwater environments. The aim is to provide a solution to large-scale scene modeling that is both accurate and efficient. To this end, we have developed a novel Structure from Motion algorithm...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Nicosevici, Tudor (Συγγραφέας), Garcia, Rafael (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Σειρά:Springer Tracts in Advanced Robotics, 87
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Nicosevici, Tudor.  |e author. 
245 1 0 |a Efficient 3D Scene Modeling and Mosaicing  |h [electronic resource] /  |c by Tudor Nicosevici, Rafael Garcia. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2013. 
300 |a XXII, 161 p. 97 illus., 76 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
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490 1 |a Springer Tracts in Advanced Robotics,  |x 1610-7438 ;  |v 87 
505 0 |a Introduction -- Literature Review -- Direct Structure from Motion -- Online Loop Detection -- Online 3D Model Simplification -- Conclusions. 
520 |a This book proposes a complete pipeline for monocular (single camera) based 3D mapping of terrestrial and underwater environments. The aim is to provide a solution to large-scale scene modeling that is both accurate and efficient. To this end, we have developed a novel Structure from Motion algorithm that increases mapping accuracy by registering camera views directly with the maps. The camera registration uses a dual approach that adapts to the type of environment being mapped.   In order to further increase the accuracy of the resulting maps, a new method is presented, allowing detection of images corresponding to the same scene region (crossovers). Crossovers then used in conjunction with global alignment methods in order to highly reduce estimation errors, especially when mapping large areas. Our method is based on Visual Bag of Words paradigm (BoW), offering a more efficient and simpler solution by eliminating the training stage, generally required by state of the art BoW algorithms.   Also, towards developing methods for efficient mapping of large areas (especially with costs related to map storage, transmission and rendering in mind), an online 3D model simplification algorithm is proposed. This new algorithm presents the advantage of selecting only those vertices that are geometrically representative for the scene. 
650 0 |a Engineering. 
650 0 |a Artificial intelligence. 
650 0 |a Image processing. 
650 0 |a Robotics. 
650 0 |a Automation. 
650 1 4 |a Engineering. 
650 2 4 |a Robotics and Automation. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
650 2 4 |a Image Processing and Computer Vision. 
700 1 |a Garcia, Rafael.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783642364174 
830 0 |a Springer Tracts in Advanced Robotics,  |x 1610-7438 ;  |v 87 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-36418-1  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)