Texture extraction from photographs and rendering with dynamic texture mapping

Date

1999-12-01

Author

Genç, Serkan
Atalay, Mehmet Volkan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

51
views

0
downloads

There is a natural trend in modeling a scene on a computer with minimum effort of the user. Wireframe modeling and texturing is the main two factors that affect the quality of results in computer graphics. In this paper, instead of 3D model reconstruction, automatic texture extraction and texture registering for surfaces are discussed. Deficiency of the artificial textures to create photorealistic results leads to us using real textures for rendering. Assuming that camera parameters, lighting conditions, 3D model and its surface properties are known and the image sequences of the scene are provided by the user, textures for surfaces can be extracted from images. Naturally, textures coming from different images need to be enhanced. Some artifacts, i.e., highlights, distortion from perspective projection should be removed. Unlike traditional texture mapping which generates a single texture for a surface, multiple textures are used in rendering. A selection mechanism enables us to choose the best texture from multiple textures according to the orientation of the viewpoint. The texture, which is mapped, is not unique and static. Therefore, it is called dynamic texture mapping. Experiments show that the results are promising. © 1999 IEEE.

Subject Keywords

Rendering (computer graphics), Layout, Surface texture, Computer graphics, Cameras, Image reconstruction, Read only memory, Animation, image enhancement, computational geometry, computer vision

URI

https://hdl.handle.net/11511/56211

DOI

https://doi.org/10.1109/iciap.1999.797737

Conference Name

Proceedings 10th International Conference on Image Analysis and Processing

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Contextualized scene modeling using boltzmann machines Bozcan, İlker; Kalkan, Sinan; Department of Computer Engineering (2018) Scene modeling is very crucial for robots that need to perceive, reason about and manipulate the objects in their environments. In this thesis, we propose a variant of Boltzmann Machines (BMs) for contextualized scene modeling. Although many computational models have been proposed for the problem, ours is the first to bring together objects, relations, and affordances in a highly-capable generative model. For this end, we introduce a hybrid version of BMs where relations and affordances are introduced with ...
Texture classification and retrieval using random neural network model Teke, Alper; Atalay, Mehmet Volkan; Department of Computer Engineering (2003) Texture is one of the most important characteristics used in computer vision and image processing applications. In this thesis, a new texture classification and retrieval method is proposed for texture analysis applications. The technique makes use of the random neural network model and it is supervised. The main aim is to represent textures with parameters which are the random neural network weights and classify and retrieve textures using this texture definition. The network has neurons that correspond to...
Efficient rendering of complex scenes on heterogeneous parallel architectures Yıldırım Kalkan, Gökçe; İşler, Veysi; Department of Computer Engineering (2014) In computer graphics, generating high-quality images at high frame rates for rendering complex scenes is a challenging task. A well-known approach to tackling this important task is to utilize parallel processing through distributing rendering and simulation tasks to different processing units. In this thesis, several methods of distributed rendering architectures are investigated, and the bottlenecks in distributed rendering are analyzed. Based on this analysis, guidelines for distributed rendering in a ne...
3D face modeling using multiple images BUYUKATALAY, SONER; Halıcı, Uğur; AKAGUNDUZ, ERDEM; ULUSOY PARNAS, İLKAY (2006-04-19) 3D face modeling based on real images is one of the important subject of Computer Vision that is studied recently. In this paper the study that eve contucted in our Computer Vision and Intelligent Systems Research Laboratory on 3D face model generation using uncalibrated multiple still images is explained.
3D face reconstruction using stereo images and structured light Öztürk, Ahmet Oğuz; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2007) Nowadays, 3D modelling of objects from multiple images is a topic that has gained great recognition and is widely used in various fields. Recently, lots of progress has been made in identification of people using 3D face models, which are usually reconstructed from multiple face images. In this thesis, a system including stereo cameras and structured light is built for the purpose of 3D modelling. The system outputs are 3D shapes of the face and also the texture information registered to this shape. Althoug...

Citation Formats

S. Genç and M. V. Atalay, “Texture extraction from photographs and rendering with dynamic texture mapping,” presented at the Proceedings 10th International Conference on Image Analysis and Processing, Venice, Italy, 1999, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56211.