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This paper proposes a systematic strategy for the automated implementation of mixed constraint- and input-output-based representations of signal processing systems. Examples of the strategy are provided in synthesizing algorithms derived from signal-flow graphs having delay-free loops, as well as in performing automated system inversion. An algorithm that follows the strategy, and which has been deployed...
Localization in global navigation satellite system denied environments using inertial sensors alone, or radio sensors alone or a combination of both are the currently active research topics. The current research works are primarily focused on static environments with earth fixed coordinate frames, having nonmoving maps. In this research work, we use micro electromechanical sensors based inertial sensors,...
In this paper a novel (t, n) threshold image secret sharing scheme is proposed. Based on the idea that there is close connection between secret sharing and coding theory, coding method on GF(2m) is applied in our scheme instead of the classical Lagrange's interpolation method in order to deal with the fidelity loss problem in the recovery. All the generated share images are meaningful and the size...
Sensor Pattern Noise (SPN) has been proved as an effective fingerprint of imaging devices to link pictures to the cameras that acquired them. In practice, forensic investigators usually extract this camera fingerprint from large image block to improve the matching accuracy because large image blocks tend to contain more SPN information. As a result, camera fingerprints usually have a very high dimensionality...
This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. Quantile analysis in pixel, wavelet, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. Noise model mismatch would likely...
In this paper, a parallel system together with an adaptive workload balancing algorithm is proposed for view synthesis on multi-core platforms. Based on system level data parallelism, an adaptive workload balancing method is proposed for depth image based rendering by evaluating the number of non-hole pixels after warping. Experimental results demonstrated that with the proposed workload balancing...
This paper addresses content based image retrieval based on color features. Several previous works have addressed color based image retrieval based on hand-crafted features. In this paper, a data-driven learning framework is proposed for generating color based signatures. To obtain the features, a linear transformation is learned from the pixel values based on its reconstruction error. Using this...
Remote imaging photoplethysmography (RIPPG) can achieve contactless human vital signs monitoring. Though the remote operation mode brings a great convenience for RIPPG applications, the RIPPG signal quality is limited by the remote nature. Improving the RIPPG signal quality becomes an essential task in the clinical application of RIPPG. Since the region of interest (ROI) of the RIPPG transforms from...
One main challenge in developing a system for visual surveillance event detection is the annotation of target events in the training data. By making use of the assumption that events with security interest are often rare compared to regular behaviours, this paper presents a novel approach by using Kullback-Leibler (KL) divergence for rare event detection in a weakly supervised learning setting, where...
View synthesis prediction (VSP) is an important tool for improving the coding efficiency in the next generation three-dimensional (3-D) video systems. However, VSP will result in a new type of inter-view error propagation when the multi-view video plus depth (MVD) data are transmitted over the lossy networks. In this paper, this new type of error propagation is characterized and modeled. Firstly,...
We study the coding efficiency of view synthesis prediction (VSP) in 3D video coding. Our spectral domain analysis relates the power spectral density (PSD) of the VSP prediction error to the probability density function (pdf) of the warping error. Our analysis takes into account the warping error induced by (i) depth coding and (ii) rounding error at integer-pel, half-pel and quarter-pel warping accuracy...
We consider the motion-compensated temporal prediction loop at the heart of modern video coders. Rather than using motion-compensated reference frame blocks directly as predictors, we incorporate their spatially-filtered versions into the prediction loop. We design adaptive filters that are geared toward successful prediction over sophisticated temporal evolutions involving lighting changes, focus...
The High Efficiency Video Coding standard (HEVC) supports a total of 35 intra prediction modes which aim at reducing spatial redundancy by exploiting pixel correlation within a local neighborhood. In this paper, we show that spatial correlation remains after intra prediction, leading to high energy prediction residues. We propose a novel scheme for encoding the prediction residues using a Mode Dependent...
HEVC uses up to 35 prediction modes for intra prediction and it can well predict blocks with uni-directional structures or sharp edges, but the intra prediction still suffers from its discontinuous characteristics. To improve coding performance of intra prediction, the inpainting technique has been studied but it is impractical because of its high computational complexity. In this paper, we employ...
In this paper, we propose a new method for singing voice detection based on a Bidirectional Long Short-Term Memory (BLSTM) Recurrent Neural Network (RNN). This classifier is able to take a past and future temporal context into account to decide on the presence/absence of singing voice, thus using the inherent sequential aspect of a short-term feature extraction in a piece of music. The BLSTM-RNN contains...
This paper investigates a multi-channel denoising autoencoder (DAE)-based speech enhancement approach. In recent years, deep neural network (DNN)-based monaural speech enhancement and robust automatic speech recognition (ASR) approaches have attracted much attention due to their high performance. Although multi-channel speech enhancement usually outperforms single channel approaches, there has been...
Monaural singing voice separation has aroused considerable attention. Many pitch-based methods have been proposed to address this task, but generally have limited performance. The most crucial difficulties lie in the inaccurate judgment on voiced pitches and the failed recognition on unvoiced singing sounds. In this paper, we propose a novel algorithm based on the latent component analysis of time-frequency...
In this paper we propose a novel approach to cepstral smoothing for reducing musical noise fluctuations in binaural speech enhancement. Similar to other methods, our approach computes a preliminary spectral gain function using the magnitude-squared coherence function and applies an instantaneous weighting to the gain function in the cepstral domain. In this contribution, the weighting function is...
Structural segmentation of music involves identifying boundaries between homogenous regions where the homogeneity involves one or more musical dimensions, and therefore depends on the musical genre. In this work, we address the segmentation of Hindustani instrumental concert recordings at the highest time-scale, that is, concert sections marked by prominent changes in rhythmic structure. Tempo features...
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