Mesh and "crack lines": application to object-based motion estimation and higher scalability

Marquant, Gwenaëlle; Pateux, Stéphane; Labit, Claude

doi:10.1109/icip.2000.899486

Cited by 12 publications

(5 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then (6) Proof: Recall that the directional derivative of a function , along a unit-directional vector , is given by where is the gradient of at . Thus, the second derivative of along at can be written as (7) where the Hessian matrix is defined by (8) with , and denoting the partial derivatives , , and , respectively. Clearly, is a real, symmetric matrix, thus the eigenvalues and eigenvectors of are also real.…”

Section: A Image Feature-map Extractionmentioning

confidence: 99%

A fast approach for accurate content-adaptive mesh generation

Yang

Wernick

Brankov

2003

IEEE Trans. on Image Process.

View full text Add to dashboard Cite

Mesh modeling is an important problem with many applications in image processing. A key issue in mesh modeling is how to generate a mesh structure that well represents an image by adapting to its content. We propose a new approach to mesh generation, which is based on a theoretical result derived on the error bound of a mesh representation. In the proposed method, the classical Floyd-Steinberg error-diffusion algorithm is employed to place mesh nodes in the image domain so that their spatial density varies according to the local image content. Delaunay triangulation is next applied to connect the mesh nodes. The result of this approach is that fine mesh elements are placed automatically in regions of the image containing high-frequency features while coarse mesh elements are used to represent smooth areas. The proposed algorithm is noniterative, fast, and easy to implement. Numerical results demonstrate that, at very low computational cost, the proposed approach can produce mesh representations that are more accurate than those produced by several existing methods. Moreover, it is demonstrated that the proposed algorithm performs well with images of various kinds, even in the presence of noise.

show abstract

Section: A Image Feature-map Extractionmentioning

confidence: 99%

A fast approach for accurate content-adaptive mesh generation

Yang

Wernick

Brankov

2003

IEEE Trans. on Image Process.

View full text Add to dashboard Cite

show abstract

“…We use a mesh-based motion estimator based on a multi-resolution scheme over hierarchical meshes. It allows dense estimation between current images I and I , by successive estimation/relaxation steps between successive images [14]. This motion estimator provides a dense motion field between I and I .…”

Section: Dense Motion Estimationmentioning

confidence: 99%

Sliding Adjustment for 3D Video Representation

Galpin

Morin

2002

EURASIP J. Adv. Signal Process.

View full text Add to dashboard Cite

This paper deals with video coding of static scenes viewed by a moving camera. We propose an automatic way to encode such video sequences using several 3D models. Contrary to prior art in model-based coding where 3D models have to be known, the 3D models are automatically computed from the original video sequence. We show that several independent 3D models provide the same functionalities as one single 3D model, and avoid some drawbacks of the previous approaches. To achieve this goal we propose a novel algorithm of sliding adjustment, which ensures consistency of successive 3D models. The paper presents a method to automatically extract the set of 3D models and associate camera positions. The obtained representation can be used for reconstructing the original sequence, or virtual ones. It also enables 3D functionalities such as synthetic object insertion, lightning modification, or stereoscopic visualization. Results on real video sequences are presented.

show abstract

“…In addition, the resulting mesh edges are expected to be well aligned with image featured (edges or corners) in order to maintain a faithful restoration of the original image. Mesh modeling of an image has many applications like image compression [1,2,3,4], motion tracking and compensation [5,6,7,8,9,10], image processing by geometric manipulation [11], medical image processing [12], feature detection [13], pattern recognition [14], computer vision [15], restoration [16], tomographic reconstruction [17], interpolation [18,19] and image/video coding [20,21,22,23,24,25].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Mesh Representation and Restoration of Biomedical Images

Liu,

Xu,

2014

Preprint

View full text Add to dashboard Cite

The triangulation of images has become an active research area in recent years for its compressive representation and ease of image processing and visualization. However, little work has been done on how to faithfully recover image intensities from a triangulated mesh of an image, a process also known as image restoration or decoding from meshes. The existing methods such as linear interpolation, least-square interpolation, or interpolation based on radial basis functions (RBFs) work to some extent, but often yield blurred features (edges, corners, etc.). The main reason for this problem is due to the isotropically-defined Euclidean distance that is taken into consideration in these methods, without considering the anisotropicity of feature intensities in an image. Moreover, most existing methods use intensities defined at mesh nodes whose intensities are often ambiguously defined on or near image edges (or feature boundaries). In the current paper, a new method of restoring an image from its triangulation representation is proposed, by utilizing anisotropic radial basis functions (ARBFs). This method considers not only the geometrical (Euclidean) distances but also the local feature orientations (anisotropic intensities). Additionally, this method is based on the intensities of mesh faces instead of mesh nodes and thus provides a more robust restoration. The two strategies together guarantee excellent feature-preserving restoration of an image with arbitrary super-resolutions from its triangulation representation, as demonstrated by various experiments provided in the paper.

show abstract

Mesh and "crack lines": application to object-based motion estimation and higher scalability

Cited by 12 publications

References 6 publications

A fast approach for accurate content-adaptive mesh generation

A fast approach for accurate content-adaptive mesh generation

Sliding Adjustment for 3D Video Representation

Adaptive Mesh Representation and Restoration of Biomedical Images

Contact Info

Product

Resources

About