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Survey: Vision-based Model generation of 3-D real world scene 김준환 , Marc Nguyen , 설창환 Nov. 05 Introduction Building 3-D Model without using wrestling with CAD tools for months ? Labor-intensive time-consuming resulting models is apparently computer-generated
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Survey: Vision-based Model generation of 3-D real world scene 김준환, Marc Nguyen, 설창환 Nov. 05
Introduction • Building 3-D Model without using wrestling with CAD tools for months ? • Labor-intensive • time-consuming • resulting models is apparently computer-generated • can’t be sure about the accuracy of the model • The Alternatives • vision-based approach • take some photos, process them, ready-to-go • 3-D scanning • not suitable for outdoor scene
Modeling Approaches Geometry(CAD) -based Vision-based
Decisions to make • Model: polygon or image? • Tightly coupled to utilization of the model • 3-D polygonal model • conventional VR walk-thru / fly-by • image-based model • image-based renderering/VR (sort of QuickTime VR™) • User input? • Fully automatic • User input as needed
Getting Polygonal models • Existing works • Depth map + textures • Hybrid approach [Devebec96] • Issues • shape-from • Stereo • Motion • something else ? • which feature to use • pixel, line, face, …
Basic PrinciplesStereo Vision(1/5) • Basic formula • reconstruction of the 3-D coordinates of a number of points in a scene for given 2 (or more) images obtained by cameras of known relative positions and orientations • Correspondence problem • given a token in image 1, what is the corresponding token in image 2?
Basic PrinciplesStereo Vision(2/5) • Constraints • epipolar constraint • for a given point in the plane 1, its possible matches in the plane 2 all lie on a line, therefore search space is reduced from 2D to 1D
Basic PrinciplesStereo Vision(3/5) • Ordering constraints • the orders of tokens in one image is preserved in the other image (not true when one token is in the forbidden region of the other token)
Basic PrinciplesStereo Vision(4/5) • Planarity constraint • if the surfaces of the objects are planar, there exists an analytic transformation from the left image coordinates to the right image coordinates.
Basic PrinciplesStereo Vision(5/5) • Limitation • still exist ambiguity • the distance between of the two camera must be sufficiently small
Basic PrinciplesModel-based Vision(1/3) • Basic principle • to recognize 3D objects, compare a scene model (constructed by processing images obtained from sensors) against entities in a model database (containing a discription of each object the system is expected to recognize).
Basic PrinciplesModel-based Vision(2/3) • Related works • Hanson and Henderson[Hans89] • the automatic synthesis of a specialized recognition scheme, called a strategy tree based on CAGD(computer aided geometric design) model. • Strategy tree • describe the search process used for recognition and localization of a particular objects in the given scene • consist of selected 3D features which satisfy system constraints and corroborating evidence subtrees which are used in the formation of hypothesis.
Basic PrinciplesModel-based Vision(3/3) • Flynn and Jain [Flyn91] • develop a system which uses 3D object descriptions created on a commercial CAD system • express in both the industry-standard IGES (initial graphics exchange specification) form and a polyhedral approximation • perform geometric inferencing to obtain a relational graph representation of the object which can be stored in a database of models for object recognition
Depth map + Textures • Not provide polygonal representation • need further processing(e.g mesh construction) • Need special H/W • 3D scanner • laser range finder • video-rate stereo machine Http://www.cyberware.com
Depth map & Texture: T.Kanade at CMU (1/3) • MBV(Modeling by Videotaping) • “Walking around the room with camcorder, and get the 3-D model of the room and the trajectory of camera” • Based on shape-from-motion • factorization technique Terrain House http://www.ius.cs.cmu.edu/IUS/mbvc0/www/modeling.html
Related works at CMU (2/3) • Z-key • generation of depth map in real time using special purpose H/W http://www.cs.cmu.edu/afs/cs/project/stereo-machine/www/StereoMachine.html
virtualized event arbitrary view merging multi-view stereo input images recording Related works at CMU (3/3) • Virtualized Reality • create virtual models of real-world events (e.g. sports) http://www.cs.cmu.edu/~virtualized-reality/
Hybrid approach for architectural scene • Modeling and Rendering Architecture from Photographs: A Hybrid Geometry- and Image-based Approach,” Proc. SIGGRAPH ‘96 • For architectural scene • Hierarchy of Block primitives • parameter reduction in first phase • affordable level in amount of user input • Model-based stereo • refine rough model to recover the details SIGGRAPH ‘96 Conference Proceedings
Hybrid approach신영길, SNU • Road and surrouding environments • Simplified case of [Debevec96] • Face feature instead of edge 컴퓨터그래픽스학회,97춘계
Image-based model • Existing works • Hirose95 • View mosaicing • Issues • how to acquire / store the 2D images ? • How to generate seamless image sequence • morphing, stitching • tightly related to image-based rendering
Hirose 95 (1/4) • Purpose • generation of virtual words by processing 2D real images taken by video cameras • Basic concept • image recording • position recording • image generation for user’s viewpoint Presence, Vol 5, No 1, http://ghidorah.t.u-tokyo.ac.jp/Projects/IBR/
Hirose 95 (2/4) Image Recording H/W
Hirose 95 (3/4) • Image synthesis system • Search for nearby images in the database • Basic operations : shift, scale, rotation of recorded image • Combination of basic operations • Enhanced system • Use multi-images interpolation • Reduce the the feeling of abrupt switch from one image to another
Hirose 95 (4/4) • Advantages of the method • easy way to generate virtual worlds • very realistic appearance • Drawbacks • No possibility of user’s interaction • Archiving volume very large • Image processing problems (speed, distortion,…) • Future works • Use of new technology for archiving virtual worlds • Generation of wide virtual worlds (world database) • evolved into CABIN?
View mosaicing • process of registering several images to obtain a single coherent image • Suitable for “looking around” style VR http://falcon.postech.ac.kr/people/narziss/image_mosaic/mosaic.html http://www.cs.cornell.edu/Info/People/kleong/mosaic.html
Szeliski96 (1/2) • Purpose • Set of techniques for building image mosaics • Virtual reality applications • Planar image mosaics • Different pictures are used to generate one wide planar image • Panoramic image mosaics • Set of images taken from one viewpoint with a rotation of the camera • Panoramic effect -> illusion of real view and scene • Used for outdoor scenic view, building interior in virtual reality applications IEEE CG&A 1996
Szeliski96 (2/2) • Projective depth recovery • Necessary for illusion of 3D • Conclusions • These techniques can be used as vision based generation of virtual worlds • Photorealistic appearance and try to restore 3D effect • But now only static applications • May be used as a part of more complete vision-based system
Summary • Getting realistic model of real world object / scene without CAD • indoor, human-scale object : 3D scanning • outdoor scene : vision-based approach • Based on computer vision techniques • human input to some degree might be very helpful • Hybrid approach • towards moving objects / realtime modeling