ENGLISH

Image-Based Modeling of Plants and Trees (Morgan & Claypool Publishers)

Book information

Publisher
Morgan & Claypool Publishers
Year
2010
ISBN
1608452441, 9781608452446, 9781608452453
Language
english
Format
PDF
Filesize
3 MB (3233879 bytes)
Series
Morgan & Claypool Publishers
Pages
83\83
Topic
Computers
Library
duansci.com
Time added
2010-05-12 16:22:54

Description

Plants and trees are among the most complex natural objects. Much work has been done attempting to model them, with varying degrees of success. In this book, we review the various approaches in computer graphics, which we categorize as rule-based, image-based, and sketch-based methods. We describe our approaches for modeling plants and trees using images. Image-based approaches have the distinct advantage that the resulting model inherits the realistic shape and complexity of a real plant or tree. We use different techniques for modeling plants (with relatively large leaves) and trees (with relatively small leaves).With plants, we model each leaf from images, while for trees, the leaves are only approximated due to their small size and large number. Both techniques start with the same initial step of structure from motion on multiple images of the plant or tree that is to be modeled. For our plant modeling system, because we need to model the individual leaves, these leaves need to be segmented out from the images. We designed our plant modeling system to be interactive, automating the process of shape recovery while relying on the user to provide simple hints on segmentation. Segmentation is performed in both image and 3D spaces, allowing the user to easily visualize its effect immediately. Using the segmented image and 3D data, the geometry of each leaf is then automatically recovered from the multiple views by fitting a deformable leaf model. Our system also allows the user to easily reconstruct branches in a similar manner. To model trees, because of the large leaf count, small image footprint, and widespread occlusions, we do not model the leaves exactly as we do for plants. Instead, we populate the tree with leaf replicas from segmented source images to reconstruct the overall tree shape. In addition, we use the shape patterns of visible branches to predict those of obscured branches. As a result, we are able to design our tree modeling system so as to minimize user intervention. We also handle the special case of modeling a tree from only a single image. Here, the user is required to draw strokes on the image to indicate the tree crown (so that the leaf region is approximately known) and to refine the recovery of branches. As before, we concatenate the shape patterns from a library to generate the 3D shape. To substantiate the effectiveness of our systems, we show realistic reconstructions of a variety of plants and trees from images. Finally, we offer our thoughts on improving our systems and on the remaining challenges associated with plant and tree modeling. Table of Contents: Introduction / Review of Plant and Tree Modeling Techniques / Image-Based Technique for Modeling Plants / Image-Based Technique for Modeling Trees / Single Image Tree Modeling / Summary and Concluding Remarks / Acknowledgments Figure Credits......Page 9 Introduction......Page 11 Rule-based methods......Page 15 Sketch-based methods......Page 19 Image-based methods......Page 21 Modeling Leaves, Flowers, and Bark......Page 23 Modeling Other Flora......Page 25 Appendix: Brief description of L-system......Page 26 Preliminary Processes......Page 29 Graph-based Leaf Extraction......Page 30 Graph partition......Page 31 Graph update......Page 33 Leaf reconstruction......Page 34 Branch Extraction and Reconstruction......Page 36 Results......Page 37 Discussion......Page 41 Summary......Page 42 Overview of the system......Page 43 Reconstruction of visible branches......Page 45 Reconstruction of occluded branches......Page 47 Image segmentation and clustering......Page 49 Adding leaves to branches......Page 51 Results......Page 52 Summary......Page 55 Image Plane Sketching......Page 59 Tree Growing......Page 63 Growth engine......Page 64 Data-driven attractors......Page 66 Results......Page 67 Summary......Page 71 Summary and Concluding Remarks......Page 73 Authors' Biographies......Page 75

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