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In this paper, different strategies for the calculation of the Harte's Harmonic Change Detection Function (HCDF) are discussed. HCDFs can be used for detecting chord boundaries for Automatic Chord Estimation (ACE) tasks, where the chord transitions are identified as peaks in the HCDF. We show that different audio features and different novelty metric have significant impact on the overall accuracy...
Recent years have shown increases in virtual 3D perception and applications, many of these applications require 3D model reconstruction from high quality LIDAR scans. High quality 3D models may be acquired from a collection of overlapping LIDAR scans which need to be registered or aligned to a common coordinate system. This paper investigates the use of a novel implementation of trilateration for...
This papers deals with supervised texture classification. The extracted features are the image second and third order moments. The number of possible moment lags for 2-D signals increases rapidly with the order of the moment even for small lag neighbourhoods. The paper focuses on the selection of moment lags that optimise classification performance. Lag selection also serves another purpose: it waives...
Photoplethysmography (PPG) signals, captured using smart phones are generally noisy in nature. Although they have been successfully used to determine heart rate from frequency domain analysis, further indirect markers like blood pressure (BP) require time domain analysis for which the signal needs to be substantially cleaned. In this paper we propose a methodology to clean such noisy PPG signals....
The best form of identifying a person for criminal investigation is from the fingerprint. Identifying suspects based on latent fingerprint is a procedure that is extremely important to forensics and law enforcement agencies. The small number of minutiae and the noise characteristic of latents make it extremely difficult to automatically match latents to their mated full prints that are stored in law...
Feature selection is not only a key to handle the high dimensionality phenomenon caused by the vector space model representation, but mainly an efficient technique to reduce the noise generated by the irrelevant and redundant terms. However, in order to effectively capture the most important features, both the semantic and the statistical information within the feature space should be taken into account...
Circular data is very relevant in many fields such as Geostatistics, Mobile Robotics and Pose Estimation. However, some existing angular regression methods do not cope with arbitrary nonlinear functions properly. Moreover, some other regression methods that do cope with nonlinear functions, like Gaussian Processes, are not designed to work well with angular responses. This paper presents two novel...
Stereo visual odometry (VO) is a common technique for estimating a camera's motion, features are tracked across frames and the pose change is subsequently inferred. This position estimation method can play a particularly important role in environments in which the global positioning system (GPS) is not available (e.g., Mars rovers). Recently, some authors have noticed a bias in VO position estimates...
A detection method of moving targets in deep space is researched based on technology of image registration. According to the characteristics of deep space image information, a SUSAN feature point extraction algorithm is modified to inhibit isolated noises which are similar to sidereal feature points, and it effectively eliminates isolated noises. The geometric constraint among stars in the star image...
This paper proposes a high accuracy and fast image restoration approach to restore a sequence of atmospheric turbulence degraded frames of a remote object or scene. A coarse-to-fine optical flow technique is employed to estimate the dense motion fields of the frames against a reference frame. The First Register Then Average And Subtract (FRTAAS) method is used to correct the geometric distortions...
This paper presents a novel feature extractor for robust large vocabulary continuous speech recognition (LVCSR) task. For accurate and robust estimation of speech power spectrum we propose to compute the features from the regularized minimum variance distortionless response (regMVDR) spectral estimate instead of the windowed periodogram estimate. A sigmoid shape subband spectrum enhancement technique...
In this paper, we address the problem of the total visual features loss during visual servoing. We present a new method allowing to reconstruct these features even if the image is completely unavailable. The proposed method has been developed for a 6 degree-of-freedom (DOF) calibrated camera and a static landmark of interest which can be characterized by point features. It relies on a predictor/corrector...
In this paper, three approaches for ego-motion estimation using Time-of-Flight (ToF) camera data are evaluated. Ego-motion is defined as a process of estimating a camera's pose relative to some initial pose using the camera's image sequence. The ToF camera is characterised with a number error models. These models are used to design several filters that are applied on point cloud data. Iterative Closest...
A new convenient calibration algorithm is proposed for unsynchronized multi-camera networks having large capture volume. The proposed method gives a simple and accurate calibration mean using a small 3D reference object. Extrinsic and intrinsic parameters are recovered simultaneously by capturing the object placed arbitrarily in different locations in the capture volume. The proposed method first...
An RGB-D camera is a sensor which outputs the distances to objects in a scene in addition to their RGB color. Recent technological advances in this area have introduced affordable devices in the robotics community. In this paper, we present a real-time feature extraction and pose estimation technique using the data from a single RGB-D camera. First, a set of edge features are computed from the depth...
In this paper, we study a set of histogram and higher-order statistical (HOS) features for automatically identifying the presence of large background in the magnitude MR images. The robustness and discriminative power of each individual feature and combining feature sets are investigated using different MR images including brain, cardiac, breast, spine, stomach and noisy images corrupted by Rician...
This paper describes a technique for enhancing the Mel-filtered log spectra of noisy speech, with application to noise robust speech recognition. We first compute an SNR-based soft-decision mask in the Mel-spectral domain as an indicator of speech presence. Then, we exploit the known time-frequency correlation of speech by treating this mask as an image, and performing median filtering and blurring...
Extraction of robust features from noisy speech signals is one of the challenging problems in Automatic Speech Recognition (ASR). For Gaussian process, its bispectrum and all higher order spectra are identically zero, which means that bispectrum removes the additive white Gaussian noise while preserving the magnitude and phase information of original signal. Using this bispectrum property, spectrum...
Precession is significant for midcourse discrimination. By modelling micro-Doppler of spatial precession cone and analysing its modulation characteristic, an instantaneous frequency estimation method based on an effective quadratic time-frequency analysis technique named S-method combined with the inverse Radon transform is proposed to extract micro-Doppler feature. Simulation results with electromagnetic...
Processing underwater acoustic signals for monitoring and classification are difficult problems that have recently attracted attention in the field of underwater signal processing. For these purposes, it is necessary to use a method which could be able to extract the useful information about the processed data. In this paper, an algorithm of extracting feature from radiated noise of underwater targets...
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