@conference {14860,
	title = {On the equivalence of common approaches to lighting insensitive recognition},
	booktitle = {Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on},
	volume = {2},
	year = {2005},
	month = {2005/10//},
	pages = {1721 -1726 Vol. 2 - 1721 -1726 Vol. 2},
	abstract = {Lighting variation is commonly handled by methods invariant to additive and multiplicative changes in image intensity. It has been demonstrated that comparing images using the direction of the gradient can produce broader insensitivity to changes in lighting conditions, even for 3D scenes. We analyze two common approaches to image comparison that are invariant, normalized correlation using small correlation windows, and comparison based on a large set of oriented difference of Gaussian filters. We show analytically that these methods calculate a monotonic (cosine) function of the gradient direction difference and hence are equivalent to the direction of gradient method. Our analysis is supported with experiments on both synthetic and real scenes},
	keywords = {3D, conditions;lighting, cosine, difference;image, direction, filters;gradient, function;image, insensitive, intensity;lighting, recognition;image, recognition;lighting, scenes;Gaussian, segmentation;, variation;monotonic},
	doi = {10.1109/ICCV.2005.179},
	author = {Osadchy,M. and Jacobs, David W. and Lindenbaum,M.}
}
@conference {14026,
	title = {The manifolds of spatial hearing},
	booktitle = {Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP {\textquoteright}05). IEEE International Conference on},
	volume = {3},
	year = {2005},
	month = {2005/03//},
	pages = {iii/285 - iii/288 Vol. 3 - iii/285 - iii/288 Vol. 3},
	abstract = {We present exploratory studies on learning the non-linear manifold structure, in head related impulse responses (HRIRs). We use the recently popular locally linear embedding technique. The lower dimensional manifold encodes the perceptual information in the HRIRs, namely the direction of the sound source. Based on this, we propose a new method for HRIR interpolation. We also propose that the distance between two HRIRs of an individual be taken as the geodesic distance on the learned manifold.},
	keywords = {acoustics;, dimensional, direction, distance;, EMBEDDING, encoding;, geodesic, Head, hearing, hearing;, HRIR, impulse, information, interpolation;, learned, linear, localization;, locally, low, manifold, manifold;, manifolds;, nonlinear, perceptual, related, response;, responses;, sound, source, spatial, structure;, technique;, transient},
	doi = {10.1109/ICASSP.2005.1415702},
	author = {Duraiswami, Ramani and Raykar,V.C.}
}
@conference {12735,
	title = {Video synthesis of arbitrary views for approximately planar scenes},
	booktitle = {Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP {\textquoteright}03). 2003 IEEE International Conference on},
	volume = {3},
	year = {2003},
	month = {2003/04//},
	pages = {III - 497-500 vol.3 - III - 497-500 vol.3},
	abstract = {In this paper, we propose a method to synthesize arbitrary views of a planar scene, given a monocular video sequence. The method is based on the availability of knowledge of the angle between the original and synthesized views. Such a method has many important applications, one of them being gait recognition. Gait recognition algorithms rely on the availability of an approximate side-view of the person. From a realistic viewpoint, such an assumption is impractical in surveillance applications and it is of interest to develop methods to synthesize a side view of the person, given an arbitrary view. For large distances from the camera, a planar approximation for the individual can be assumed. In this paper, we propose a perspective projection approach for recovering the direction of motion of the person purely from the video data, followed by synthesis of a new video sequence at a different angle. The algorithm works purely in the image and video domain, though 3D structure plays an implicit role in its theoretical justification. Examples of synthesized views using our method and performance evaluation are presented.},
	keywords = {(access, 3D, applications;, approach;, approximately, approximation;, arbitrary, Biometrics, control);, data;, direction, estimation;, evaluation;, Gait, image, monocular, MOTION, performance, perspective, planar, processing;, projection, recognition;, recovery;, scenes;, sequence;, sequences;, side, signal, structure;, Surveillance, surveillance;, synthesis;, synthesized, video, view, views;},
	doi = {10.1109/ICASSP.2003.1199520},
	author = {Chowdhury, A.K.R. and Kale, A. and Chellapa, Rama}
}
@conference {18156,
	title = {A recognition algorithm for Chinese characters in diverse fonts},
	booktitle = {Image Processing. 2002. Proceedings. 2002 International Conference on},
	volume = {3},
	year = {2002},
	month = {2002/06//},
	pages = {981 - 984 vol.3 - 981 - 984 vol.3},
	abstract = {The paper proposes an algorithm for recognizing Chinese characters in many diverse fonts including Song, Fang, Kai, Hei, Yuan, Lishu, Weibei and Xingkai. The algorithm is based on features derived from peripheral direction contributions and utilizes a set of dictionaries. A 3-level matching is first performed with respect to each dictionary. The distance measures associated with these matches are then fed into a central discriminator to output the final recognition result. We propose a new multi-dictionary matching algorithm for use in the central discriminator that utilizes estimated information of neighborhood fonts. Experiments have been performed on a practical OCR software system whose recognition kernel is based on the proposed algorithm. Fast and accurate recognition has been accomplished both in title recognition, involving all of the 8 fonts, and in main-body recognition, that usually involves only the first 4 most commonly used fonts.},
	keywords = {algorithm;, central, character, Chinese, contributions;, direction, discriminator;, diverse, fonts;, image, interfaces;, LANGUAGE, MATCHING, matching;, multi-dictionary, natural, OCR, optical, peripheral, recognition, recognition;, sets;, software, system;},
	doi = {10.1109/ICIP.2002.1039139},
	author = {Wu,Xianli and M. Wu}
}
