&lt;title&gt;Object-based video coding using forward-tracking 2D mesh layers&lt;/title&gt;

Beek, P.J.L. van; Tekalp, A.M.

doi:10.1117/12.263282

Cited by 18 publications

(9 citation statements)

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“…In the experiment the first step of the search required only five recursive steps to find the correct position. We also compared our method with existing approaches reported in [11] and [1], [4], [6], respectively. Both methods were developed for tracking objects in video.…”

Section: Resultsmentioning

confidence: 99%

“…One can see that the block method locates the object, but provides no information about the deformation of the object while our method does both. In [1], [4], and [6], an object is represented by a hierarchical 2-D or 3-D mesh consisting of Delaunay triangles. The mesh is tracked by applying simple block matching method individually to each node or by optical flow method.…”

Section: Resultsmentioning

confidence: 99%

“…By convolving an image with Gabor wavelets the Gabor wavelet transform (GWT) of the image can be defined as: (6) Referring to (1), one may observe that the output of the GWT is a complex number. There are a total of different frequencies and different orientations, resulting in coefficients for each image pixel .…”

Section: Gabor Function Gabor Wavelets and Local Featuresmentioning

confidence: 99%

“…In content-based video compression, in order to save bits representing the shape and motion vectors of an object, two-dimensional (2-D) or three-dimensional (3-D) mesh based algorithms have been used [1], [3], [4], [6]. The idea is to represent an object by a set of nodes and connecting line segments which usually form triangles.…”

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confidence: 99%

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Object tracking using the Gabor wavelet transform and the golden section algorithm

Zheng

Ahalt

2002

IEEE Trans. Multimedia

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Abstract-This paper presents an object tracking method for object-based video processing which uses a two-dimensional (2-D) Gabor wavelet transform (GWT) and a 2-D golden section algorithm. An object in the current frame is modeled by local features from a number of the selected feature points, and the global placement of these feature points. The feature points are stochastically selected based on the energy of their GWT coefficients. Points with higher energy have a higher probability of being selected since they are visually more important. The amplitudes of the GWT coefficients of a feature point are then used as the local feature. This takes advantage of the characteristics of Gabor wavelets which are highly localized in both the time and the frequency domains. The global placement of the feature points is determined by a 2-D mesh whose feature is the area of the triangles formed by the feature points. In this way, a local feature is represented by a GWT coefficient amplitude vector, and a global feature is represented by a triangle area vector. One advantage of the 2-D mesh is that the direction of its triangle area vector is invariant to affine transform. Consequently, the similarity between two local features or two global features can be defined as a function of the angle and the length ratio between two vectors, and the overall similarity between two objects is a weighted sum of the local and global similarities. In order to find the corresponding object in the next frame, the 2-D golden section algorithm is employed, and this can be shown to be the fastest algorithm to find the maximum of a unimodal function. Our results show that the method is robust to object deformation and supports object tracking in noisy video sequences.Index Terms-Content-based video, feature points, Gabor wavelets, golden section, mesh, object-based video, object tracking.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Gabor Function Gabor Wavelets and Local Featuresmentioning

confidence: 99%

mentioning

confidence: 99%

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Object tracking using the Gabor wavelet transform and the golden section algorithm

Zheng

Ahalt

2002

IEEE Trans. Multimedia

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“…In the CGI technique, a small number of points in motion, called the grid points (GPs), are first estimated so as to minimize the MC error, then whole frame is motion-compensated, by interpolating the motions between the GPs. An object-based CGI technique was also proposed in [7], employing triangular meshes to cope with the complex motions. But, [7] cannot exploit the local image characteristics effectively.…”

Section: Introductionmentioning

confidence: 99%