A novel speech enhancement system based on wavelet packet decomposition (WPD) is proposed. Noise level is estimated based on quantile in wavelet threshold domain. To handle colored and non-stationary noises, the universal thresholds are weighted by a time-frequency dependent nonlinear function. Two nonlinear weighting methods using temporal threshold variation and kernel smoothing are proposed....

A PCA based gait segmentation method is proposed. Background images are used for PCA training. PCA reconstruction, recursive error compensation and single threshold based method is put forward for gait segmentation. Single threshold based method has the same gait segmentation ability as classical adaptive threshold based method, and the former is faster in implementation than the later. Propose...

We propose a fast disparity estimation algorithm using background registration and object segmentation for stereo sequences from fixed cameras. Dense background disparity information is calculated in an initialization step so that only disparities of moving object regions are updated in the main process. We propose a real-time segmentation technique using background subtraction and inter-frame ...

This paper describes an optimization strategy based on a perceptual assessment criterion for dereverberation algorithms. The complete procedure is applied to the adaptive inversefiltering (AIF) and spectral subtraction (SS) stages of a given dereverberation algorithm using the so-called QAreverb quality measure. Experimental results, using a 204-signal speech database, indicate that the associa...

Multi-component recording contains full wavefield information that can be used in polarization filtering to attenuate surface-wave noise. The polarization filter used here is a station-by-station approach that combines statics, signal-to-noise ratio, and eigenimages to construct a surfacewave noise model and then applies an adaptive subtraction to remove the noise. Statics and signal-to-noise r...

This paper presents a novel vision based obstacle detection algorithm that is adapted from a powerful background subtraction algorithm: ViBe (VIsual Background Extractor). We describe an adaptive obstacle detection method using monocular color vision and an ultrasonic distance sensor. Our approach assumes an obstacle free region in front of the robot in the initial frame. However, the method dy...

Detecting people or other articulated objects and localizing their body parts is a challenging computer vision problem as their movement is unpredictable under circumstances of partial and full occlusions. In this paper, a framework for human body parts tracking in video sequences using a self-adaptive cluster background subtraction (CBS) scheme is proposed based on a Gaussian mixture model (GM...

Simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can be used to non-invasively measure the spatiotemporal dynamics of the human brain. One challenge is dealing with the artifacts that each modality introduces into the other when the two are recorded concurrently, for example the ballistocardiogram (BCG). We conducted a preliminary comparison ...

The aim of the study was to develop methods for moving vehicle tracking in aerial image sequences taken over urban areas. The first image of the sequence was manually registered to a map. Corner points were extracted semi-automatically, then tracked along the sequence, to enable video stabilisation by homography estimation. Moving objects were detected by means of adaptive background subtractio...

In this paper we describe a system that suppresses the acoustic interference due to the coupling between the microphone and the loudspeakers of a hands-free multi-channel desktop audio system. The proposed system operates in the Short-Time Fourier Transform domain and uses spectral subtraction to suppress the unwanted interference, which consists of the local audio and the remote speech signal ...