Measuring image quality is an interesting and challenging area of research. In this paper we investigate the performance of the statistical functions called copula as image quality measures. These functions are popula...
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ISBN:
(纸本)9781479900312
Measuring image quality is an interesting and challenging area of research. In this paper we investigate the performance of the statistical functions called copula as image quality measures. These functions are popular for applications where data distributions are unknown. This property motivated some researchers to using these copulas in image processing in general and in detecting image changes and image registration in particular. In this research, we use the Gaussian copula to calculate the mutual information, which is the measure of the association of the reference and the distorted or tampered with images. To test the performance of the proposed method, we implemented our method on LIVE image database and compared our results with three popular image quality measures namely Visual Information Fidelity (VIF), Structural Similarity (SSIM), and Universal Quality Measure (UQI). The results show that our quality measure, obtained similar results to the three methods in 99% of the time, hence the proposed method can be considered as an efficient image quality index.
Statistical human body models, like SCAPE, capture static 3D human body shapes and poses and are applied to many computer Vision problems. Defined in a statistical context, their parameters do not explicitly capture s...
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Statistical human body models, like SCAPE, capture static 3D human body shapes and poses and are applied to many computer Vision problems. Defined in a statistical context, their parameters do not explicitly capture semantics of the human body shapes such as height, weight, limb length, etc. Having a set of semantic parameters would allow users and automated algorithms to sample the space of possible body shape variations in a more intuitive way. Therefore, in this paper we propose a method for re-parameterization of statistical human body models such that shapes are controlled by a small set of intuitive semantic parameters. These parameters are learned directly from the available statistical human body model. In order to apply any arbitrary animation to our human body shape model we perform retargeting. From any set of 3D scans, a semantic parametrized model can be generated and animated with the presented methods using any animation data. We quantitatively show that our semantic parameterization is more reliable than standard semantic parameterizations, and show a number of animations retargeted to our semantic body shape model.
An emerging form of telecollaboration utilizes situated or mobile displays at a physical destination to virtually represent remote visitors. An example is a personal telepresence robot, which acts as a physical proxy ...
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ISBN:
(纸本)9781450310154
An emerging form of telecollaboration utilizes situated or mobile displays at a physical destination to virtually represent remote visitors. An example is a personal telepresence robot, which acts as a physical proxy for a remote visitor, and uses cameras and microphones to capture its surroundings, which are transmitted back to the visitor. We propose the use of spherical displays to represent telepresent visitors at a destination. We suggest that the use of such 360° displays in a telepresence system has two key advantages: it is possible to understand the identity of the visitor from any viewpoint;and with suitable graphical representation, it is possible to tell where the visitor is looking from any viewpoint. In this paper, we investigate how to optimally represent a visitor as an avatar on a spherical display by evaluating how varying representations are able to accurately convey head gaze. Copyright 2012 ACM.
While touch interfaces have become more popular, they are still mostly conned to mobile platforms such as smart phones and notebooks. Mouse interfaces still dominate desktop platforms due to their portability, ergonom...
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In this paper, we present an image watermarking scheme based on discrete wavelet transform and singular value decomposition (SVD) for color Images. This scheme embeds the watermark into the luminance (Y) channel of YC...
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ISBN:
(纸本)9780889869264
In this paper, we present an image watermarking scheme based on discrete wavelet transform and singular value decomposition (SVD) for color Images. This scheme embeds the watermark into the luminance (Y) channel of YC bCR color space of the host image. The luminance image is decomposed up to four DWT levels. SVD is applied on the HL1-4 and LH1-4sub-bands of each level and pseudo random number (PRN) sequence is added to the singular values of their coefficients to produce what we call modified singular values. To obtain the modified HL and LH coefficients, we take the inverse of the SVD of the modified SVs. Finally, we perform the IDWT on the modified HL & LH coefficients as well as HH and LL coefficients to produce the watermarked Y channel image. Then, the modified luminance, Cb and Cr are combined to get the watermarked color image. Simulation results show that our watermark is robust against high JPEG compression, filtering, Gaussian-noise, resizing and other image processing attacks. In addition, this watermark is not susceptible to any false positive or detection of false reference watermark.
Digital watermarking is one of the effective technology which can protect the copyright of digital product and data security. For the encoding technology of color image, this paper proposed a method for embedding the ...
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The visualisation of vector fields is essential for many applications in science, engineering and biomedicine. A large number of vector icons has been developed, but little research has been done on their effectivenes...
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Surface models derived from medical image data often exhibit artifacts, such as noise and staircases, which can be reduced by applying mesh smoothing filters. Usually, an iterative adaption of smoothing parameters to ...
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Humans have dreamed for centuries to control their surroundings solely by the power of their minds. These aspirations have been captured by multiple science fiction creations, such as the Neuromancer novel by William ...
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ISBN:
(纸本)9783939897460
Humans have dreamed for centuries to control their surroundings solely by the power of their minds. These aspirations have been captured by multiple science fiction creations, such as the Neuromancer novel by William Gibson or the Brainstorm cinematic movie, to name just a few. Nowadays, these dreams are slowly becoming reality due to a variety of brain-computer interfaces (BCI) that detect neural activation patterns and support the control of devices by brain signals. An important field in which BCIs are being successfully integrated is the interaction with vehicular systems. In this paper, we evaluate the performance of BCIs, more specifically a commercial electroencephalographic (EEG) headset in combination with vehicle dashboard systems, and highlight the advantages and limitations of this approach. Further, we investigate the cognitive load that drivers experience when interacting with secondary in-vehicle devices via touch controls or a BCI headset. As in-vehicle systems are increasingly versatile and complex, it becomes vital to capture the level of distraction and errors that controlling these secondary systems might introduce to the primary driving process. Our results suggest that the control with the EEG headset introduces less distraction to the driver, probably as it allows the eyes of the driver to remain focused on the road. Still, the control of the vehicle dashboard by EEG is efficient only for a limited number of functions, after which increasing the number of in-vehicle controls amplifies the detection of false commands.
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