@article {14023,
	title = {Speaker Localization Using Excitation Source Information in Speech},
	journal = {Speech and Audio Processing, IEEE Transactions on},
	volume = {13},
	year = {2005},
	month = {2005/09//},
	pages = {751 - 761},
	abstract = {This paper presents the results of simulation and real room studies for localization of a moving speaker using information about the excitation source of speech production. The first step in localization is the estimation of time-delay from speech collected by a pair of microphones. Methods for time-delay estimation generally use spectral features that correspond mostly to the shape of vocal tract during speech production. Spectral features are affected by degradations due to noise and reverberation. This paper proposes a method for localizing a speaker using features that arise from the excitation source during speech production. Experiments were conducted by simulating different noise and reverberation conditions to compare the performance of the time-delay estimation and source localization using the proposed method with the results obtained using the spectrum-based generalized cross correlation (GCC) methods. The results show that the proposed method shows lower number of discrepancies in the estimated time-delays. The bias, variance and the root mean square error (RMSE) of the proposed method is consistently equal or less than the GCC methods. The location of a moving speaker estimated using the time-delays obtained by the proposed method are closer to the actual values, than those obtained by the GCC method.},
	keywords = {correlation, correlation;, cross, Delay, error, error;, estimation;, excitation, generalized, information;, localization;, mean, methods;, processing;, production;, root, source, speaker, speech, square, TIME},
	isbn = {1063-6676},
	doi = {10.1109/TSA.2005.851907},
	author = {Raykar,V.C. and Yegnanarayana,B. and Prasanna,S. R.M and Duraiswami, Ramani}
}
@article {12748,
	title = {Optimal edge-based shape detection},
	journal = {Image Processing, IEEE Transactions on},
	volume = {11},
	year = {2002},
	month = {2002/11//},
	pages = {1209 - 1227},
	abstract = {We propose an approach to accurately detecting two-dimensional (2-D) shapes. The cross section of the shape boundary is modeled as a step function. We first derive a one-dimensional (1-D) optimal step edge operator, which minimizes both the noise power and the mean squared error between the input and the filter output. This operator is found to be the derivative of the double exponential (DODE) function, originally derived by Ben-Arie and Rao (1994). We define an operator for shape detection by extending the DODE filter along the shape{\textquoteright}s boundary contour. The responses are accumulated at the centroid of the operator to estimate the likelihood of the presence of the given shape. This method of detecting a shape is in fact a natural extension of the task of edge detection at the pixel level to the problem of global contour detection. This simple filtering scheme also provides a tool for a systematic analysis of edge-based shape detection. We investigate how the error is propagated by the shape geometry. We have found that, under general assumptions, the operator is locally linear at the peak of the response. We compute the expected shape of the response and derive some of its statistical properties. This enables us to predict both its localization and detection performance and adjust its parameters according to imaging conditions and given performance specifications. Applications to the problem of vehicle detection in aerial images, human facial feature detection, and contour tracking in video are presented.},
	keywords = {1D, 2D, aerial, analysis;, boundary, conditions;, contour, cross, detection;, DODE, double, edge, edge-based, error, error;, exponential, extraction;, facial, feature, filter, filter;, Filtering, function;, geometry;, global, human, images;, imaging, localization, mean, methods;, NOISE, operator;, optimal, optimisation;, output;, performance;, pixel;, power;, propagation;, properties;, section;, SHAPE, square, squared, statistical, step, theory;, tracking;, two-dimensional, vehicle, video;},
	isbn = {1057-7149},
	doi = {10.1109/TIP.2002.800896},
	author = {Moon, H. and Chellapa, Rama and Rosenfeld, A.}
}
