Autonomous model building is a crucial trend in model based methods like AAMs. This paper introduces an approach that deals with non-linearities by detecting distinct sub-parts in the data. Sub-models each representin...
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ISBN:
(纸本)1901725294
Autonomous model building is a crucial trend in model based methods like AAMs. This paper introduces an approach that deals with non-linearities by detecting distinct sub-parts in the data. Sub-models each representing an individual sub-part are derived from a minimum description length criterion. Thereby the resulting clique of models is more compact and obtains a better generalization behavior than a single model. The proposed AAM clique generation deals with non-linearities in the data in a generic information theoretic manner reducing the necessity of user interaction during training.
While considering a mirror and light rays coming either from a point source or from infinity,the reflected light rays may have an envelope,called a caustic *** this paper,we study developable surfaces as *** caustic s...
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While considering a mirror and light rays coming either from a point source or from infinity,the reflected light rays may have an envelope,called a caustic *** this paper,we study developable surfaces as *** caustic surfaces,described in a closed form,are also developable surfaces of the same type as the original mirror *** provide efficient,algorithmic computation to find the caustic surface of each of the three types of developable surfaces(cone,cylinder,and tangent surface of a spatial curve).We also provide a potential application of the results in contemporary free-form architecture design.
Human activity recognition from movement-related signals or image sequences is a quite challenging problem in computer vision. Human activities can be decoded from various set of communication channels but it is prove...
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Human activity recognition from movement-related signals or image sequences is a quite challenging problem in computer vision. Human activities can be decoded from various set of communication channels but it is proved that the head has a highlighted role to emphasize the message that is being communicated. Recognizing activities from head movements can be suitable, because the head has a near constant shape and appearance during the communication. The spatiotemporal segmentation of head movements can be also done by analyzing the trajectories. In this study, we give a general model for description and recognition of head movements. The basic idea has been extended by introducing a human activity database to make better decisions during the recognition. The proposed approach takes into consideration facial regions that encode essential information about head movements. The essence of head movements is extracted from motion history image representation and aligned by dynamic time warping. The efficiency of our system is also demonstrated by the recognition of head-drawn letters.
With widespread of the Internet as well as the numerous applications that involve audio signals and systems, the issue of ownership proof become imperative. In this paper, we present an audio watermark scheme that is ...
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With widespread of the Internet as well as the numerous applications that involve audio signals and systems, the issue of ownership proof become imperative. In this paper, we present an audio watermark scheme that is based on Empirical Mode Decomposition and Hilbert Huang Transform. The audio signal is decomposed into several mono-component signals or Intrinsic Mode Functions to serve as the addressee for watermark. The watermark is a pseudo random number which is added to the highest and lowest Intrinsic Mode Functions of the signal to generate what we call the modified IMFs which is in turn added to the remaining IMFs to produce the watermarked signal. Our experimental results show that the proposed method is robust against signal processing attacks such as MP3, time scale modification, resizing, and others. The obtained results meet the recommended imperceptibility signal to noise ratio.
We present evaluation results with focus on combined image and efficiency performance of the Gradient Network Method to segment color images, especially images showing outdoor scenes. A brief review of the techniques,...
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We present evaluation results with focus on combined image and efficiency performance of the Gradient Network Method to segment color images, especially images showing outdoor scenes. A brief review of the techniques, Gradient Network Method and Color Structure Code, is also presented. Different region-growing segmentation results are compared against ground truth images using segmentation evaluation indices Rand and Bipartite Graph Matching. These results are also confronted with other well established segmentation methods (EDISON and JSEG). Our preliminary results show reasonable performance in comparison to several state-of-art segmentation techniques, while also showing very promising results comparatively in the terms of efficiency, indicating the applicability of our solution to real time problems.
Skeleton extraction is essential for general shape representation. A typical skeletonization algorithm should obtain the ability to preserve original object's topological and hierarchical properties. However, most...
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This paper presents a work that is part of the system for creation of real-faced avatar for emphatic communication. We have made a new extension of the KL T (Kanade-Lucas-Tomasi) face tracker. which is robust against ...
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ISBN:
(纸本)9789549641332
This paper presents a work that is part of the system for creation of real-faced avatar for emphatic communication. We have made a new extension of the KL T (Kanade-Lucas-Tomasi) face tracker. which is robust against loss of the tracked points. Stochastic skin-color model is used for a face segmentation in the frames contained in a video sequence. Ellipse-fitting is used for selection of the face candidates because of the elliptical face shape. The proposed method achieved real-time performance The results seem very promising.
In this paper, we propose a near minimum sparse pattern coding based scheme for binary image compression. Sparse patterns such as those obtained from prediction, image differencing, and other methods can be coded effi...
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In this paper, we propose a near minimum sparse pattern coding based scheme for binary image compression. Sparse patterns such as those obtained from prediction, image differencing, and other methods can be coded efficiently using the scheme proposed in this paper. In this research we apply our scheme on coordinate representation of rectangular regions via a number of matrices. Such representations allow for efficiently coding these vertices, and hence compress the image significantly. Simulation results show that the proposed scheme outperformed previously published methods for coordinate data coding by nearly 17%. This scheme has low complexity compared with JBIG2.
Spline curve and surface play an important role in CAD and computergraphics. In this paper, we propose several extensions of cubic uniform B-spline. Then, we present the extensions of interpolating α-B-spline based ...
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Spline curve and surface play an important role in CAD and computergraphics. In this paper, we propose several extensions of cubic uniform B-spline. Then, we present the extensions of interpolating α-B-spline based on the new B-splines and the singular blending technique. The advantage of the extensions is that they have global and local shape parameters. Furthermore, we also investigate their applications in data interpolation and polygonal shape deformation.
作者:
Lele ZhouSaif ZahirImage Processing
Graphics and Multimedia Lab Computer Science Department University of Northern British Columbia Canada
Binary image compression is desirable for a wide range of applications, such as digital libraries, map archives, fingerprint databases, facsimile, etc. In this paper, we present a new highly efficient algorithm for lo...
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Binary image compression is desirable for a wide range of applications, such as digital libraries, map archives, fingerprint databases, facsimile, etc. In this paper, we present a new highly efficient algorithm for lossless binary image compression. The proposed algorithm introduces a new method, direct redundancy elimination, to efficiently exploit the two-dimensional redundancy of an image, as well as a novel dynamic context model to improve the efficiency of arithmetic coding. Simulation results show that the proposed algorithm has comparable compression ratio to JBIG standard. In many cases, the proposed algorithm outperforms the JBIG standard
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