From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

A summary of many of the new techniques developed in the last two decades for spectrum analysis of discrete time series is presented in this tutorial. An examination of the underlying time series model assumed by each technique serves as the common basis for understanding the differences among the various spectrum analysis approaches. Techniques discussed include the classical periodogram, classical Blackman-Tukey, autoregressive (maximum entropy), moving average, autotegressive-moving average, maximum likelihood, Prony, and Pisarenko methods. A summary table in the text provides a concise overview for all methods, including key references and appropriate equations for computation of each spectral estimate.

Spectrum analysis&#8212;A modern perspective

The recent advances in radio and em beddedsystem technologies have enabled the proliferation of wireless microsensor networks. Such wirelessly connected sensors are released in many diverse environments to perform various monitoring tasks. In many such tasks, location awareness is inherently one of the most essential system parameters. It is not only needed to report the origins of events, but also to assist group querying of sensors, routing, and to answer questions on the network coverage. In this paper we present a novel approach to the localization of sensors in an ad-hoc network. We describe a system called AHLoS (Ad-Hoc Localization System) that enables sensor nodes to discover their locations using a set distributed iterative algorithms. The operation of AHLoS is demonstrated with an accuracy of a few centimeters using our prototype testbed while scalability and performance are studied through simulation.

Dynamic fine-grained localization in Ad-Hoc networks of sensors

A vector quantizer is a system for mapping a sequence of continuous or discrete vectors into a digital sequence suitable for communication over or storage in a digital channel. The goal of such a system is data compression: to reduce the bit rate so as to minimize communication channel capacity or digital storage memory requirements while maintaining the necessary fidelity of the data. The mapping for each vector may or may not have memory in the sense of depending on past actions of the coder, just as in well established scalar techniques such as PCM, which has no memory, and predictive quantization, which does. Even though information theory implies that one can always obtain better performance by coding vectors instead of scalars, scalar quantizers have remained by far the most common data compression system because of their simplicity and good performance when the communication rate is sufficiently large. In addition, relatively few design techniques have existed for vector quantizers. During the past few years several design algorithms have been developed for a variety of vector quantizers and the performance of these codes has been studied for speech waveforms, speech linear predictive parameter vectors, images, and several simulated random processes. It is the purpose of this article to survey some of these design techniques and their applications.

Vector quantization

Information Theory and Reliable Communication

Space-time coding is a promising channel coding technique for wireless communications. Combined with antenna diversity, space-time coding can provide improved performance while maintaining the same data transmission rate, which makes it an attractive candidate for high-data-rate transmission systems such as orthogonal frequency division multiplexing (OFDM) systems. In this paper, we compare the performance of space-time coded OFDM systems with that of OFDM systems defined by IEEE 802.11a over AWGN channels and slow fading channels. Although space-time block coding does not have coding gain, it can be used as an inner coding method to obtain diversity gain. Space-time trellis coding obtains 1 dB coding gain and 9 dB diversity gain.

Performance of OFDM systems with space-time coding

In 1960 Campbell used a version of the asymptotic equipartition property (AEP) to derive a relationship between the entropy of the source power spectral density and the minimum coefficient rate required to encode the source. Abramson (1985) subsequently provided a brief discussion of Campbell's coefficient rate and a qualitative comparison to the mean squared prediction error of samples taken at the Nyquist rate. Mester and Franke (1992) investigated the spectral entropy as an alternative measure of energy compaction in transform coding. Otherwise there has been very little interest in spectral entropy in the literature. We analyse the spectral entropy and compare it to the familiar entropy rate power for autoregressive processes. We also discuss a possible limitation on its utility for a class of random processes. >

What is the interpretation of spectral entropy

In this paper, we propose a new statistical objective perceptual video quality measure PSNR r,f -MOSr. PSNR r,f is defined as the PSNR achieved by f% of the frames in each one of the r% of the transmissions over a network. This quantity has the potential to capture the performance loss due to damaged frames in a particular video sequence (f%), as well asto indicate the probablity of a user experiencing a specified quality over the channel (r%). The percentage of transmissions also has the interpretation as what percentage out of many video users who access the same channel, would experience a given video quality. A subjective experiment is conducted to establish a linear equation connecting PSNR r,f=90% and MOS r , the mean opinion score (MOS) achieved by r% of the transmissions. It is shown from this subjective experiment that PSNR f=90% correlates much better with the delivered perceptual video quality than the average PSNR across all frames of a video, and is a good representation of perceptual quality of a video transmitted over networks with possible transmission errors.

PSNR r,f -MOS r : An easy-to-compute multiuser perceptual video quality measure

One of Shannon's many fundamental contributions was his result that source coding and channel coding can be implemented separately without any loss of optimality. However, the assumption underlying this result may at times be violated in practice. Various joint source/channel coding approaches have been developed for handling such situations. A MAP approach to joint source/channel coding has been proposed which uses a MAP decoder and a modification of the source coder to provide error correction. We present various implementation strategies for this approach and provide results for an image coding application.

Implementation Issues In Map Joint Source/channel Coding

This paper describes a new method to automatically improve scene lighting for video conferencing by learning the photometric mapping between a lower exposure and desired exposure created using High Dynamic Range (HDR) imaging techniques. Once the mapping is learned in a calibration step, it can be used to transform all subsequent images, effectively producing higher dynamic range video without ghosting artifacts. A stereo algorithm is also described that allows multiple exposures to be taken at every frame, useful if the lighting of a scene changes significantly. Results show that this is an effective way to improve face lighting and therefore the overall experience of video conferencing.

Jerry D. Gibson

Papers

Performance of OFDM systems with space-time coding

What is the interpretation of spectral entropy

PSNR r,f -MOS r : An easy-to-compute multiuser perceptual video quality measure

Implementation Issues In Map Joint Source/channel Coding

Automatic scene relighting for video conferencing