Compactly Supported Wavelets Derived From Legendre Polynomials: Spherical Harmonic Wavelets

A new family of wavelets is introduced, which is associated with Legendre polynomials. These wavelets, termed spherical harmonic or Legendre wavelets, possess compact support. The method for the wavelet construction is derived from the association of ordinary second order differential equations with multiresolution filters. The low-pass filter associated with Legendre multiresolution analysis is a linear phase finite impulse response filter (FIR).Comment: 6 pages, 6 figures, 1 table In: Computational Methods in Circuits and Systems Applications, WSEAS press, pp.211-215, 2003. ISBN: 960-8052-88-

Interactive speech-driven facial animation

One of the fastest developing areas in the entertainment industry is digital animation. Television programmes and movies frequently use 3D animations to enhance or replace actors and scenery. With the increase in computing power, research is also being done to apply these animations in an interactive manner. Two of the biggest obstacles to the success of these undertakings are control (manipulating the models) and realism. This text describes many of the ways to improve control and realism aspects, in such a way that interactive animation becomes possible. Specifically, lip-synchronisation (driven by human speech), and various modeling and rendering techniques are discussed. A prototype that shows that interactive animation is feasible, is also described.Mr. A. Hardy Prof. S. von Solm

Frequency shifts and depth dependence of premotor beta band activity during perceptual decision-making

Neural activity in the premotor and motor cortices shows prominent structure in the beta frequency range (13–30 Hz). Currently, the behavioral relevance of this beta band activity (BBA) is debated. The underlying source of motor BBA and how it changes as a function of cortical depth are also not completely understood. Here, we addressed these unresolved questions by investigating BBA recorded using laminar electrodes in the dorsal premotor cortex of 2 male rhesus macaques performing a visual reaction time (RT) reach discrimination task. We observed robust BBA before and after the onset of the visual stimulus but not during the arm movement. While poststimulus BBA was positively correlated with RT throughout the beta frequency range, prestimulus correlation varied by frequency. Low beta frequencies (∼12–20 Hz) were positively correlated with RT, and high beta frequencies (∼22–30 Hz) were negatively correlated with RT. Analysis and simulations suggested that these frequency-dependent correlations could emerge due to a shift in the component frequencies of the prestimulus BBA as a function of RT, such that faster RTs are accompanied by greater power in high beta frequencies. We also observed a laminar dependence of BBA, with deeper electrodes demonstrating stronger power in low beta frequencies both prestimulus and poststimulus. The heterogeneous nature of BBA and the changing relationship between BBA and RT in different task epochs may be a sign of the differential network dynamics involved in cue expectation, decision-making, motor preparation, and movement execution.Published versio

A Comprehensive Review on Multimedia Retrieval Techniques

Abstract: With the prevalence of sight and sound advancements and web mediums, client can't fulfil with the customarey techniques for data retrieval systems. On account of this, the substance based picture recovery is turning into another and quick strategy for data recovery. Substance based picture recovery is the system for recovering the information especially pictures from a wide gathering of databases. The recovery is careried out by utilizing highlights. Content Based Image Retrieval (CBIR) is a system to compose the wide mixture of pictures by their visual highlight. Feature based recovery or retrieval procedures aree accessible for recovering the pictures, in our review we aree investigating them. In our first segment, we aree tending towareds a few nuts and bolts of a specific CBIR framework with that we have demonstrated some fundamental highlights of any picture, these aree similare to shape, surface, shading and indicated diverse systems to compute them. We have also demonstrated diverse separeation measuring systems utilized for closeness estimation of any picture furthermore talked about indexing methods. At last conclusion and future degree is examined. DOI: 10.17762/ijritcc2321-8169.15061

Active Vision With Multiresolution Wavelets

A wavelet decomposition for multiscale edge detection is used to separate border edges from texture in an image, toward the goal of a complete segmentation by Active Perception for robotic exploration of a scene. The physical limitations of the image acquisition system and the robotic system provide the limitations on the range of scales which we consider. We link edges through scale space, using the characteristics of these wavelets for guidance. The linked zero crossings are used to remove texture and preserve borders, then the scene can be reconstructed without texture

Regularity scalable image coding based on wavelet singularity detection

In this paper, we propose an adaptive algorithm for scalable wavelet image coding, which is based on the general feature, the regularity, of images. In pattern recognition or computer vision, regularity of images is estimated from the oriented wavelet coefficients and quantified by the Lipschitz exponents. To estimate the Lipschitz exponents, evaluating the interscale evolution of the wavelet transform modulus sum (WTMS) over the directional cone of influence was proven to be a better approach than tracing the wavelet transform modulus maxima (WTMM). This is because the irregular sampling nature of the WTMM complicates the reconstruction process. Moreover, examples were found to show that the WTMM representation cannot uniquely characterize a signal. It implies that the reconstruction of signal from its WTMM may not be consistently stable. Furthermore, the WTMM approach requires much more computational effort. Therefore, we use the WTMS approach to estimate the regularity of images from the separable wavelet transformed coefficients. Since we do not concern about the localization issue, we allow the decimation to occur when we evaluate the interscale evolution. After the regularity is estimated, this information is utilized in our proposed adaptive regularity scalable wavelet image coding algorithm. This algorithm can be simply embedded into any wavelet image coders, so it is compatible with the existing scalable coding techniques, such as the resolution scalable and signal-to-noise ratio (SNR) scalable coding techniques, without changing the bitstream format, but provides more scalable levels with higher peak signal-to-noise ratios (PSNRs) and lower bit rates. In comparison to the other feature-based wavelet scalable coding algorithms, the proposed algorithm outperforms them in terms of visual perception, computational complexity and coding efficienc