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This work introduces a set of tools for motion pattern analysis in video surveillance. For a given video stream, first the motion trajectories are extracted and an affinity matrix is constructed. Then, motion pattern analysis is conducted based on Normalized Spectral Clustering. An Eigengap based methodology is proposed for determining the number of clusters. It was observed that in real life scenarios,...
Recently studies have been performed on spectral features such as Mel Frequency Cepstral Coefficients (MFCC) and Linear Predictor Cepstral Coefficients (LPCC) for speech emotion recognition. It was found in our study that the Fourier Transform of MFCC time trajectories also play an important role in speech emotion recognition. And also a new hierarchical classification method was proposed based on...
This paper proposes a technique for human face recognition based on improved Principal Component Analysis (PCA). Specifically the proposed method apprehends the unsupervised PCA technique and transforms it into a supervised classification approach by imparting feedback of the classification correctness of each of the principal components obtained. The proposed method trounces the disadvantages of...
Although important and effective contributions on face recognition under varying facial expressions have been reported up to date, most of the methods need multiple images of an individual stored in the database. However, this problem becomes more challenging when a limited number of training samples are available as is the case for expression invariant face identification for surveillance and security...
We propose a new Non-Intrusive Load Monitoring (NILM) approach for appliances power profile/signal estimation at low sampling rate (1 s or greater). The proposed method relay on two main phases: identification of turned on appliance combination in a given time period and estimation of the active power consumption signal of each individual appliances in that combination. Unlike most existing NILM method...
Electromagnetic torque of a DC motor can be measured directly by a torque sensor attached to the shaft. However, this is an expensive solution requiring additional power, interfacing and sometimes such a torque sensor can be too bulky to be implemented in a compact environment. Alternatively, the armature current measurement can be used to derive the electromagnetic torque of the DC motor, provided...
This paper presents the work on developing a controller for the three wheeled omni-directional mobile robot for the operation on a flat terrain. Central to a robot base are omni-directional wheels. In addition to providing traction normal to the rotor axis like an ordinary wheel, they are capable of sliding parallel to the rotor axis without much friction. We have designed and implemented a robot...
A Non-Intrusive Load Monitoring (NILM) method for residential appliances based on uncorrelated spectral components of an active power signal is presented. This method utilizes the Karhunen Loéve (KL) expansion to breakdown the active power signal into subspace components so as to construct a unique information rich appliance signature. Unlike existing NILM techniques that rely on multiple measurements...
A real-time event tracking method is proposed that is immune to background variances. The proposed method models each pixel as a collection of Gaussian distributions to handle background variations and uses manipulations in the RGB space to mitigate the effects of foreground shadows. A two stepped connected component analysis method is also introduced in refining the estimated foreground and clustering...
Obstacle detection and map generation is an essential tool for site reconnaissance applications. Further it enables optimal and efficient path planning for mobile agents to navigate in unknown environments. This paper proposes a solution to this problem through a stereo vision-based obstacle detection and depth measurement method for reconnaissance. The proposed approach employs a boundary tracing...
This paper presents a subspace signature based approach for the identification of turned on appliances at a given observation time using one single-function smart meter. The novelty of the proposed approach compared to existing method is its capability for proper identification while relying on a significantly lower amount of measurement data. Unlike existing techniques which rely on multiple measurements...
This paper addresses the specific problem of human event detection from a video sequence in both indoor and outdoor environments. Foreground image pixels are identified through the principle of background subtraction by defining a reference background model using a mixture of time varying Gaussian distributions. Color filtering in the RGB space is then used to remove image distortions due to camera...
This paper addresses the generic object counting problem with object overlapping occurring at varied levels and degrees. The overall image containing the objects is segmented from the background. Thereafter a combination of parameters is extracted from each of the segments to construct a parameter space. The overall space formed by these vectors contains redundant dimensions due to the existence of...
This paper presents a dynamic, subspace based approach for extraction and classification of non-stationary acoustic signals under noisy conditions. The stationary subspace methods commonly used for noise removal take the whole signal into consideration while determining the signal subspace. This, for a non-stationary signal implies that spectral variations that occur through time are not taken into...
The focus of this work is the development of an efficient adaptive algorithm for source separation from a noisy image sequence with interferences when the underlying source signals are unknown. The sources to be extracted are the underlying activation signals who are collectively responsible for the intensity fluctuations of the pixels. This technique uses the concept of temporal Independent Component...
In this paper an adaptive modified decision-directed algorithm (MDDA) for the electronic polarization control of the polarization-multiplexed coherent optical QPSK transmission is proposed. The algorithm utilizes a variable control gain instead of a fixed control gain. Simulations with a coherent QPSK transmission system show that this algorithm converges faster and experience minimum local oscillations...
Extraction of unknown independent source signals from a noisy mixture is a fundamental problem in most signal processing applications. The existing independent component analysis (ICA) algorithms have tackled this problem for complex and real valued mixtures for both super and sub Gaussian sources. However in reality super and sub Gaussian sources exist collectively in a mix. It was observed when...
The performance of interference cancellation systems based on Wiener filters relies on proper modeling of the channel between the adaptive filter input and the reference signal. Once the optimal condition is achieved the correlated interference signal components are cancelled out and the desired signal can be extracted as the Wiener filter error signal. In practice, for most applications, the signals...
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