A novel image restoration algorithm is presented in this paper. The restoration problem is formulated under the energy minimization framework and is solved using a dynamic programming-based approach. Through applying ...
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ISBN:
(纸本)9780769527864
A novel image restoration algorithm is presented in this paper. The restoration problem is formulated under the energy minimization framework and is solved using a dynamic programming-based approach. Through applying dynamic programming iteratively along both horizontal and vertical scanlines, the new algorithm can quickly converge to a near-global optimal solution, without suffering the so-called streak artifacts. Experiments on both grayscale and color images demonstrate that the presented algorithm can effectively remove Gaussian noise and impulse noise from corrupted images, as well as to restore images with missing intensity values.
This paper introduces a novel method to simulate B-mode medical ultrasound speckle in synthetic images. Our approach takes into account both the ultrasound image formation model and the speckle formation model. The al...
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ISBN:
(纸本)9780769527864
This paper introduces a novel method to simulate B-mode medical ultrasound speckle in synthetic images. Our approach takes into account both the ultrasound image formation model and the speckle formation model. The algorithm first modifies the geometry of an ideal noiseless image to match that of a sectoral B-mode ultrasonogram, by subsampling a grid of pixels to simulate the acquisition and quantization steps of image formation. Then, speckle is added by simulating a random walk in the plane of the complex amplitude, according to the Burckhardt speckle formation model. We finally interpolate the noisy subsampled pixels in order to fill the space introduced by the sampling step and recover a complete image, as would a real ultrasonograph. Synthetic speckle images generated by this method are visually and theoritically very close to real ultrasonograms.
In this paper we propose a novel object tracking algorithm in video sequences. The formulation of the object tracking is based on variational calculus, where an adaptive parametric mixture model is used for object fea...
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ISBN:
(纸本)9780769527864
In this paper we propose a novel object tracking algorithm in video sequences. The formulation of the object tracking is based on variational calculus, where an adaptive parametric mixture model is used for object features representation. The tracking is based on matching the object mixture models between successive frames of the sequence by using active contours while adapting the mixture model to varying object appearance changes due to illumination conditions and camera geometry. The implementation of the method is based on level set active contours which allow for automatic topology changes and stable numerical schemes. We validate our approach on examples of object tracking performed on real video sequences.
Realization of new surgical treatment in the 21st century, it is necessary to use various advanced technologies;surgical robots, three-dimensional medical images, computer graphics, computer simulation technology and ...
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ISBN:
(纸本)9783540730439
Realization of new surgical treatment in the 21st century, it is necessary to use various advanced technologies;surgical robots, three-dimensional medical images, computer graphics, computer simulation technology and others. Three-dimensional medical image for surgical operation provides surgeons with advanced vision. A surgical robot provides surgeons with advanced hand, but it is not a machine to do the same action of a surgeon using scissors or a scalpel. The advanced vision and hands available to surgeons are creating new surgical fields, which are minimally invasive surgery, non-invasive surgery, virtual reality microsurgery, tele-surgery, fetus surgery, neuro-informatics surgery and others in the 21st century.
We describe a video indexing system that aims at indexing large video files in relation to the presence of similar faces. The detection of near-frontal view faces is done with a cascade of weak classifier. Face tracki...
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ISBN:
(纸本)9780769527864
We describe a video indexing system that aims at indexing large video files in relation to the presence of similar faces. The detection of near-frontal view faces is done with a cascade of weak classifier. Face tracking is done through a particle filter and generate trajectories. Face clusters are found based on a spectral clustering approach. We compare the performance of various spectral clustering techniques based on 2DPCA features. The system performance is evaluated against a public face database as well as on a real full-length feature movie.
Multi-modal imaging sensors are employed in advanced surveillance systems in the recent years. The performance of surveillance systems can be enhanced by using information beyond the visible spectrum, for example, inf...
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ISBN:
(纸本)9780769527864
Multi-modal imaging sensors are employed in advanced surveillance systems in the recent years. The performance of surveillance systems can be enhanced by using information beyond the visible spectrum, for example, infrared imaging. To ensure correctness of low- or high-level processing, multi-modal imagers must be fully calibrated or registered. In this paper, an algorithm is proposed to register the video sequences acquired by an infrared and an electro-optical (CCD) camera. The registration method is based on the silhouette extracted by differencing adjacent frames. This difference is found by an image structural similarity measurement. Initial registration is implemented by tracing the top head points in consecutive frames. Finally, an optimization procedure to maximize mutual information is employed to refine the registration results.
This paper describes a construct that we call a face image log. Face image logs are collections of time stamped images representing faces detected in surveillance videos. The techniques demonstrated in this paper stri...
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In this paper we present a framework for 3D hand tracking and dynamic gesture recognition using a single camera. Hand tracking is performed in a two step process: we first generate 3D hand posture hypothesis using geo...
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In this paper, we propose a finite mixture model of generalized Gaussian distributions (GDD) for robust segmentation and data modeling in the presence of noise and outliers. The model has more flexibility to adapt the...
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ISBN:
(纸本)9780769527864
In this paper, we propose a finite mixture model of generalized Gaussian distributions (GDD) for robust segmentation and data modeling in the presence of noise and outliers. The model has more flexibility to adapt the shape of data and less sensibility for over-fitting the number of classes than the Gaussian mixture. In a first part of the present work, we propose a derivation of the Maximum-Likelihood estimation of the parameters of the new mixture model and we propose an information-theory based approach for the selection of the number of classes. In a second part, we propose some applications relating to image, motion and foreground segmentation to measure the performance of the new model in image data. modeling with comparison to the Gaussian mixture.
In this paper, we propose a robust video foreground modeling by using a finite mixture model of generalized Gaussian distributions (GDD). The model has a flexibility to model the video background in the presence of su...
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ISBN:
(纸本)9780769527864
In this paper, we propose a robust video foreground modeling by using a finite mixture model of generalized Gaussian distributions (GDD). The model has a flexibility to model the video background in the presence of sudden illumination changes and shadows, allowing for an efficient foreground segmentation. In a first part of the present work, we propose a derivation of the online estimation of the parameters of the mixture of GDDS and we propose a Bayesian approach for the selection of the number of classes. In a second part, we show experiments of video foreground segmentation demonstrating the performance of the proposed model.
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