Relief occlusion-adaptive meshes for 3D imaging

Wan

Proceedings of the ACM Symposium on Virtual Reality Software and Technology

2004

An important, potential application of image-based techniques is to create photo-realistic image-based environments for interactive walkthrough. However, existing image-based studies are based on different assumptions with different focuses. There is a lack of a general framework or architecture for evaluation and development of a practical image-based system. In this paper, we propose an architecture to unify different image-based methods. Based on the architecture, we propose an image-based system to support interactive walkthrough of scalable environments. In particular, we introduce the concept of angular range, which is useful for designing a scalable configuration, recovering geometric proxy as well as rendering. We also propose a new method to recover geometry information even from outdoor scenes and a new rendering method to address the problem of abrupt visual changes in a scalable environment.

“…To deal with the representation problem, we apply the Relief Occlusion-Adaptive Mesh (ROAM) [19] here. ROAM can be considered as a set of hybrid 3D-2D meshes.…”

Section: Roam Formationmentioning

confidence: 99%

Modeling and rendering of walkthrough environments with panoramic images

Wan

Proceedings of the ACM Symposium on Virtual Reality Software and Technology

2004

“…The output of the image registration process is represented by a geometric proxy, called relief occlusion-adaptive mesh (ROAM) [36], for rendering. A ROAM is a hybrid 2-D/3-D mesh.…”

Section: G Geometric Proxy Representation and Renderingmentioning

confidence: 99%

“…For the nonmatched triangular meshes, they represent the occluded regions visible only to individual images and hence they are simply modeled as 2-D meshes for the images. After storing the image registration result as ROAM's, arbitrary views can be generated using a rendering algorithm such as [36].…”

Section: G Geometric Proxy Representation and Renderingmentioning

confidence: 99%

Image registration for image-based rendering

IEEE Trans. on Image Process.

2005

Self Cite

Abstract-Image-based rendering (IBR) has received much attention in recent years for its ability to synthesize photo-realistic novel views. To support translational motion, existing IBR methods either require a large amount of reference images or assume that some geometric information is available. However, rendering with a large amount of images is very expensive in terms of image acquisition, data storage, and memory costs. As IBR accepts various kinds of geometric proxy, we may use image registration techniques, such as stereo matching and structure and motion recognition, to obtain geometric information to help reduce the number of images required. Unfortunately, existing image registration techniques only support a small search range and require closely sampled reference images. This results in a high spatial sampling rate, making IBR impractical for use in scalable walkthrough environments.Our primary objective of this project is to develop an image registration technique that would recover the geometric proxy for IBR while, at the same time, reducing the number of reference images required. In this paper, we analyze the roles and requirements of an image registration technique for reducing the spatial sampling rate. Based on these requirements, we present a novel image registration technique to automatically recover the geometric proxy from reference images. With the distinguishing feature of supporting a large search range, the new method can accurately identify correspondences even though the reference images may only be sparsely sampled. This can significantly reduce the acquisition effort, the model size, and the memory cost.Index Terms-Image-based rendering (IBR), image matching, image registration, object recognition.

“…Our method considers both the modeling process and the rendering process together. In the modeling process, we extend the image-based representation scheme called Relief Occlusion-Adaptive Mesh (ROAM), which we developed earlier [Siu03], to store the recovered geometric proxy. We also propose an image registration technique called Adaptive Mesh Segmentation (AMS) for constructing the geometric proxy.…”

Section: Introductionmentioning

confidence: 99%

Image-based modeling and rendering with geometric proxy

Proceedings of the 12th Annual ACM International Conference on Multimedia

2004

In this paper, we present an image-based method to recover a geometric proxy and generate novel views. We use an integrated modeling and rendering approach to deal with the difficulty of modeling, and reduce the sampling rate. Our system is based on two novel techniques. First, we propose the Adaptive Mesh Segmentation (AMS) technique for recovering geometric proxy of a scene environment. Second, we propose the Trifocal Morphing technique for efficient rendering with the geometric proxy, which can handle non-matched regions of the scene. Our method allows images to be sparsely captured and thus highly reduces the manual image acquisition effort as well as the data size.