Qualitative Motion Understanding by Wilhelm Burger, Bir Bhanu.

Mobile robots operating in real-world, outdoor scenarios depend on dynamic scene understanding for detecting and avoiding obstacles, recognizing landmarks, acquiring models, and for detecting and tracking moving objects. Motion understanding has been an active research effort for more than a decade,...

Full description

Saved in:
Bibliographic Details
Main Authors: Burger, Wilhelm (Author), Bhanu, Bir (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York, NY : Springer US : Imprint: Springer, 1992.
Edition:1st ed. 1992.
Series:The Springer International Series in Engineering and Computer Science, 184
Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.

MARC

LEADER 00000nam a22000005i 4500
001 b3232015
003 MWH
005 20191027191100.0
007 cr nn 008mamaa
008 121227s1992 xxu| s |||| 0|eng d
020 |a 9781461535669 
024 7 |a 10.1007/978-1-4615-3566-9  |2 doi 
035 |a (DE-He213)978-1-4615-3566-9 
050 4 |a E-Book 
072 7 |a UYQV  |2 bicssc 
072 7 |a COM016000  |2 bisacsh 
072 7 |a UYQV  |2 thema 
100 1 |a Burger, Wilhelm.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Qualitative Motion Understanding  |h [electronic resource] /  |c by Wilhelm Burger, Bir Bhanu. 
250 |a 1st ed. 1992. 
264 1 |a New York, NY :  |b Springer US :  |b Imprint: Springer,  |c 1992. 
300 |a XIII, 210 p.  |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 
347 |a text file  |b PDF  |2 rda 
490 1 |a The Springer International Series in Engineering and Computer Science,  |x 0893-3405 ;  |v 184 
490 1 |a Springer eBook Collection 
505 0 |a 1 Introduction -- 1.1 Aims of Motion Understanding -- 1.2 Autonomous Land Vehicle Navigation -- 1.3 Multi-Level Vision and Motion Analysis -- 1.4 Approaches to Motion Understanding -- 1.5 Outline of this Book -- 2 Framework for Qualitative Motion Understanding -- 2.1 Moving Through a Changing Environment -- 2.2 The “DRIVE” Approach -- 2.3 Low-Level Motion -- 2.4 Camera Motion and Scene Structure -- 2.5 Detecting 3-D Motion -- 2.6 Qualitative Modeling and Reasoning -- 3 Eli ECTS OF CAMERA MOTION -- 3.1 Viewing Geometry -- 3.2 Effects of Camera Rotation -- 3.3 Computing the Camera Rotation Angles -- 3.4 Effects of Camera Translation -- 3.5 Computing the Translation Parameters -- 4 Decomposing Image Motion -- 4.1 Motion Between Successive Frames -- 4.2 FOE from Rotations -- 4.3 Rotations from FOE -- 5 THE FUZZY FOE -- 5.1 Avoiding Unrealistic Precision -- 5.2 Defining the Fuzzy FOE -- 5.3 Computing the Fuzzy FOE -- 5.4 Experiments -- 6 Reasoning about Structure and Motion -- 6.1 Abstracting Image Events -- 6.2 Interpreting Image Events -- 6.3 Reasoning About 3-D Scene Structure -- 6.4 Reasoning About 3-D Motion -- 7 The Qualitative Scene Model -- 7.1 Basic Elements of the Model -- 7.2 Representing Multiple Interpretations -- 7.3 Conflict Resolution -- 7.4 Dynamic Evolution of the QSM -- 8 EXAMPLES -- 8.1 Simulated Data -- 8.2 Real Data -- 8.3 Implementation Issues -- 9 SUMMARY -- A.1 Geometric Constraint Method for Camera Motion -- A.2 Estimating Absolute Velocity -- REFERENCES. 
520 |a Mobile robots operating in real-world, outdoor scenarios depend on dynamic scene understanding for detecting and avoiding obstacles, recognizing landmarks, acquiring models, and for detecting and tracking moving objects. Motion understanding has been an active research effort for more than a decade, searching for solutions to some of these problems; however, it still remains one of the more difficult and challenging areas of computer vision research. Qualitative Motion Understanding describes a qualitative approach to dynamic scene and motion analysis, called DRIVE (Dynamic Reasoning from Integrated Visual Evidence). The DRIVE system addresses the problems of (a) estimating the robot's egomotion, (b) reconstructing the observed 3-D scene structure; and (c) evaluating the motion of individual objects from a sequence of monocular images. The approach is based on the FOE (focus of expansion) concept, but it takes a somewhat unconventional route. The DRIVE system uses a qualitative scene model and a fuzzy focus of expansion to estimate robot motion from visual cues, to detect and track moving objects, and to construct and maintain a global dynamic reference model. 
590 |a Loaded electronically. 
590 |a Electronic access restricted to members of the Holy Cross Community. 
650 0 |a Optical data processing. 
650 0 |a Artificial intelligence. 
650 0 |a Control engineering. 
650 0 |a Robotics. 
650 0 |a Mechatronics. 
690 |a Electronic resources (E-books) 
700 1 |a Bhanu, Bir.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
830 0 |a The Springer International Series in Engineering and Computer Science,  |x 0893-3405 ;  |v 184 
830 0 |a Springer eBook Collection. 
856 4 0 |u https://holycross.idm.oclc.org/login?auth=cas&url=https://doi.org/10.1007/978-1-4615-3566-9  |3 Click to view e-book 
907 |a .b32320152  |b 04-18-22  |c 02-26-20 
998 |a he  |b 02-26-20  |c m  |d @   |e -  |f eng  |g xxu  |h 0  |i 1 
912 |a ZDB-2-ENG 
912 |a ZDB-2-BAE 
950 |a Engineering (Springer-11647) 
902 |a springer purchased ebooks 
903 |a SEB-COLL 
945 |f  - -   |g 1  |h 0  |j  - -   |k  - -   |l he   |o -  |p $0.00  |q -  |r -  |s b   |t 38  |u 0  |v 0  |w 0  |x 0  |y .i21451801  |z 02-26-20 
999 f f |i e793d9ff-e6f2-5139-8a29-72325135a736  |s 6776c2a4-fe13-57a8-a9a5-1218b0b7c15b 
952 f f |p Online  |a College of the Holy Cross  |b Main Campus  |c E-Resources  |d Online  |e E-Book  |h Library of Congress classification  |i Elec File  |n 1