Visual Attention Computational Model Based on Tracking Target

中文摘要：借鉴心理学中有关视觉注意的研究成果，提出一种应用于视频图像序列的注意焦点计算模型。针对Itti 模型算法计算复杂度高、运算速度慢等缺点，通过对注意焦点的跟踪来降低计算量，实现注意焦点的实时监测。利用相邻帧之间的相似性，通过加权颜色直方图，以最大匹配度作为预测模型，得到下一帧注意焦点的位置。实验结果表明，该注意焦点计算鲁棒性较好，可以满足动态场景实时监测的需要。 英文摘要：This paper proposes a model of the focus of attention in video sequences. The Itti model has the complex and slow computation, so it reduces computation to monitor the focus of attention through tracking the focus of attention. It uses the similarity between the adjacent frames,establishes the color histogram, selects the maximum similarity as predicable model, and gets position of the focus of attention in the next fame. The experimental results indicate that this model is effective in robustness and real-time.基金项目：国家“863”计划基金资助项目(2006AA 01Z129)；国家自然科学基金资助项目(60672018

目标跟踪的视觉注意计算模型

借鉴心理学中有关视觉注意的研究成果，提出一种应用于视频图像序列的注意焦点计算模型。针对Itti 模型算法计算复杂度高、 运算速度慢等缺点，通过对注意焦点的跟踪来降低计算量，实现注意焦点的实时监测。利用相邻帧之间的相似性，通过加权颜色直方图， 以最大匹配度作为预测模型，得到下一帧注意焦点的位置。实验结果表明，该注意焦点计算鲁棒性较好，可以满足动态场景实时监测的 需要。国家“863”计划基金资助项目(2006AA 01Z129)；国家 自然科学基金资助项目(60672018

Multiple description framework for digital watermarking

The computer age has changed the way information is stored, distributed, and even used. A significant amount of information is now stored in a digital format. Digital information has two interesting properties: copies possess the same quality as the original and distribution of information is very easy and inexpensive. With earlier technologies this was not the case, when information was copied, the copy was of poorer quality then the original. Distribution of information could be difficult as well as expensive. Copyright infringement did occur, but with relatively small occurrences. That is not the case with digital information; the copyright can be infringed upon thousands and even millions of people in a very short period of time. This has brought about the need for copyright protection, this is known as Digital Watermarking. Digital Watermarking provides a method to determine ownership of digital information. There are various types of Digital Watermarking, based on the type of information being protected, for instance: text, visual, or audio. We propose a Digital Watermarking technique that can be used for visual and audio data. This method extends a channel coding method, Multiple Description Coding, to Digital Watermarking. This method allows the user to insert a Digital Watermark and the extract this watermark without the original data. This can allow the owner the ability to prove ownership of information without exposing the original non-modified data

Optimal Filter Banks for Multiple Description Coding: Analysis and Synthesis

Multiple description (MD) coding is a source coding technique for information transmission over unreliable networks. In MD coding, the coder generates several different descriptions of the same signal and the decoder can produce a useful reconstruction of the source with any received subset of these descriptions. In this paper, we study the problem of MD coding of stationary Gaussian sources with memory. First, we compute an approximate MD rate distortion region for these sources, which we prove to be asymptotically tight at high rates. This region generalizes the MD rate distortion region of El Gamal and Cover (1982), and Ozarow (1980) for memoryless Gaussian sources. Then, we develop an algorithm for the design of optimal two-channel biorthogonal filter banks for MD coding of Gaussian sources. We show that optimal filters are obtained by allocating the redundancy over frequency with a reverse "water-filling" strategy. Finally, we present experimental results which show the effectiveness of our filter banks in the low complexity, low rate regim

Index Assignment for N Balanced Multiple Description Scalar Quantization

In this paper, we address the design of any number of balanced multiple descriptions using the multiple description scalar quantization(MDSQ) technique. The proposed scheme has the advantages of low complexity, the possibility of being extended easily to any number of descriptions and the possibility to trade off between the side, partial and central distortions. Unlike existing schemes, it can produce balanced descriptions at low rates, at the price however of a slightly higher distortion. The behavior of the proposed index assignment at high rate is in the same time similar to state-of-the-art schemes. The proposed scheme offers the possibility to adapt to loss probability, and rate constraints, in playing with both the number of descriptions, and the rate of each of them, to minimize the average distortion. The comparison with the systematic FEC (N; k) scheme shows that the FEC scheme in general gives smaller average distortion, but that our scheme seems to be more robust to sudden changes in network conditions and that receiving all the descriptions in general gives smaller distortions

Evaluate multiple description coding as an image processing method for transferring information in error-prone networks with low transmission rate, related to quality, bit rate and file size

Masteroppgave i informasjons- og kommunikasjonsteknologi 2005 - Høgskolen i Agder, GrimstadOver the past several years, image transmissions and other multimedia services have become increasingly popular. The problem is that many of these services are performed in so-called unreliable transmission systems, for example wireless or mobile systems, where there is a greater probability of packet loss, bit errors and/or interference when compared to wired transmission systems. In today’s transmission systems, retransmission is a commonly used technique for the correction of lost, or erroneous, data packets. However, this technique has several shortcomings since the retransmissions often lead to a considerable amount of extra network traffic, which in turn results in a reduced availability of bandwidth for each user, and, at worst, may result in network congestion. The time spent on data retransmissions may also be a problem in several applications. This thesis evaluates MD coding as an alternative solution to the abovementioned problems. MD coding is a technique to achieve robust communication over unreliable channels such as a lossy packet network. A source is split into two or more equally important descriptions in such a way that various reconstruction qualities are obtained from different subsets of the descriptions. In MD coding, statistical redundancy is added to a data signal in such a way that data packets, which are lost or exposed to errors during transmission, can be estimated from all, or some of, the successfully received data packets. This evaluation is accomplished by development and implementation of several SD and MD coding algorithms, where the main objective is to prove that the MD coding algorithms may considerably reduce the need for retransmission in unreliable transmission systems. Since the available bandwidth in such systems is often limited, compression of image data is also an important part of this thesis. The developed coding algorithms and compression procedures are implemented through a test application, which simulates image network transmissions with user-defined parameters. Finally, the efficiency of each developed MD coding algorithm is proved by comparing them with the SD coding systems, the so-called baseline systems. Through this thesis project, it has been discovered, by means of qualitative and quantitative tests, that the MD coding systems outperform the SD coding systems when packet loss occur during image transmission, while matching the SD coding systems when all the image data are successfully transmitted. This is done by adding a certain amount of redundancy to the MD data signals