A general non-parametric technique is proposed for the analysis of a complex multimodal feature space and to delineate arbitrarily shaped clusters in it. The basic computational module of the technique is an old pattern recognition procedure: the mean shift. For discrete data, we prove the convergence of a recursive mean shift procedure to the nearest stationary point of the underlying density function and, thus, its utility in detecting the modes of the density. The relation of the mean shift procedure to the Nadaraya-Watson estimator from kernel regression and the robust M-estimators; of location is also established. Algorithms for two low-level vision tasks discontinuity-preserving smoothing and image segmentation - are described as applications. In these algorithms, the only user-set parameter is the resolution of the analysis, and either gray-level or color images are accepted as input. Extensive experimental results illustrate their excellent performance.

Mean shift: a robust approach toward feature space analysis

Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

Digital Watermarking

/pdf/a-break-in-the-clouds-towards-a-cloud-definition-svovsw1r5a.pdf

A Break in the Clouds: Towards a Cloud Definition

A morphable model for the synthesis of 3D faces

In this paper, we define and explore proofs of retrievability (PORs). A POR scheme enables an archive or back-up service (prover) to produce a concise proof that a user (verifier) can retrieve a target file F, that is, that the archive retains and reliably transmits file data sufficient for the user to recover F in its entirety.A POR may be viewed as a kind of cryptographic proof of knowledge (POK), but one specially designed to handle a large file (or bitstring) F. We explore POR protocols here in which the communication costs, number of memory accesses for the prover, and storage requirements of the user (verifier) are small parameters essentially independent of the length of F. In addition to proposing new, practical POR constructions, we explore implementation considerations and optimizations that bear on previously explored, related schemes.In a POR, unlike a POK, neither the prover nor the verifier need actually have knowledge of F. PORs give rise to a new and unusual security definition whose formulation is another contribution of our work.We view PORs as an important tool for semi-trusted online archives. Existing cryptographic techniques help users ensure the privacy and integrity of files they retrieve. It is also natural, however, for users to want to verify that archives do not delete or modify files prior to retrieval. The goal of a POR is to accomplish these checks without users having to download the files themselves. A POR can also provide quality-of-service guarantees, i.e., show that a file is retrievable within a certain time bound.

PORs: Proofs of Retrievability for Large Files

A GOP-flexible multiview video coding (MVC) scheme based on Wyner-Ziv (WZ) coding with adaptive side information (SI) is proposed in this paper. In this scheme, each view is WZ encoded independently at the encoder side, while the views are jointly decoded at the decoder side. Therefore, the communications of different cameras can be avoided at the encoder side. In WZ coding, SPIHT and LDPC are applied to improve compression efficiency. Meanwhile, a flexible MVC structure which can satisfy different bit rate requirements and an adaptive SI selection mechanism which better utilizes temporal and interview correlations to obtain more accurate SI are proposed. The experimental results show better rate-distortion performance of the proposed scheme than other tested schemes.

GOP-flexible distributed multiview video coding with adaptive side information

The application of tabu search approach to energy allocation and index assignment for VQ-based binary phase shift keying

The paper presents a reversible watermark scheme based on hash function and lossless compression technology. The paper extracts the abstract information of the image as hash code and lossless compresses the LSB(Least Significant Bit) of the image to make some space where the image hash can be completely inserted. It needs to be done without introducing a large distortion to the image. The scheme can achieve the authentication purpose by hash code and restores the original image by retrieving the watermark sequence completely because of the lossless decompression of the LSB of the image.

A reversible watermark scheme combined with hash function and lossless compression

Stereo video can bring people into more vivid and actual sense, but the video data is too huge to storage and transmit conveniently. In this paper, a compatible scheme which compresses stereo video with flexible prediction structure is proposed. In the proposed scheme, we define a group of picture (GOP) considering of the real time of the video. There are different prediction structures according to temporal correlation and interview correlation whether the length of GOP is fixed. In any possible prediction structures, temporal correlations and interview correlations are utilized effectively. H.264 which is the most advanced video compression standard at present is utilized to improve the coding efficiency. The proposed scheme is compatible with the present equipments which are based on H.264 and process traditional monoview video. Therefore, the present equipments can process stereo video sequences conveniently. At last, the efficiency of the proposed scheme is proved by the experiment

Compatible Stereo Video Coding with Flexible Prediction Mode

Local Preserving Projection (LPP) is an unsupervised feature extraction method which considers the nearest neighbor information and has little to do with the class information, and it fails to perform well for the nonlinear problems due to its limitation of linearity. In this paper, we extend LPP to propose a novel feature extraction namely Kernel Locally Discriminant Projection (KLDP) by considering class label information and the nonlinear problems. The main work lies in: 1) the class label information is considered to create the similarity measure for the local structure graph; 2) the class-wise cosine similarity measure is applied to solve the selection of the free parameter of the similarity measure; 3) kernel method is applied to solve limitation of linearity of LPP. Besides some theory derivation, the experiments are implemented on ORL and Yale face database to evaluate the feasibility of the proposed algorithm.

Jeng-Shyang Pan

Papers

GOP-flexible distributed multiview video coding with adaptive side information

The application of tabu search approach to energy allocation and index assignment for VQ-based binary phase shift keying

A reversible watermark scheme combined with hash function and lossless compression

Compatible Stereo Video Coding with Flexible Prediction Mode

Locally Discriminant Projection with Kernels for Feature Extraction