Job C. Oostveen

Feature Extraction and a Database Strategy for Video Fingerprinting

This paper presents the concept of video fingerprinting as a tool for video identification. As such, video fingerprinting is an important tool for persistent identification as proposed in MPEG-21. Applications range from video monitoring on broadcast channels to filtering on peer-to-peer networks to meta-data restoration in large digital libraries. We present considerations and a technique for (i) extracting essential perceptual features from moving image sequences and (ii) for identifying any sufficiently long unknown video segment by efficiently matching the fingerprint of the short segment with a large database of pre-computed fingerprints.

Adaptive quantization watermarking

Although quantization index modulation (QIM) schemes are optimal from an information theoretic capacity-maximization point of view, their robustness may be too restricted for widespread practical usage. Most papers assume that host signal samples are identically distributed from a single source distribution and therefore, they do not need to consider local adaptivity. In practice there may be however several reasons for introducing locally varying watermark parameters. In this paper, we study how the Scalar Costa Scheme (which we take as a representative member of the class of QIM schemes) can be adapted to achieve practical levels of robustness and imperceptibility. We do this by choosing the basic watermark parameters on the basis of a perceptual model. An important aspect is the robustness of the statistic on which the adaptation rule is based. The detector needs to be able to accurately re-estimate the value of the parameters as used by the embedder, even in the presence of strong channel noise. One way to achieve this is to base the adaptation rule on an aggregate of the pixel values in a neighborhood around the relevant pixel. We present an analysis of the robustness-locality trade-off, based on a model for the bit error probability.

An efficient database search strategy for audio fingerprinting

In this paper we present a highly efficient audio fingerprinting system. At the core of the presented system are a highly robust fingerprint extraction method an a very efficient fingerprint search strategy, which enable searching a large fingerprint database eith only limited computing resources. We describe the main principles of the method, as well as a model for false acceptance rates.

Strongly stabilizable distributed parameter systems

Questions about stability arise in almost every control problem. There are many physical problems in which exponential stability is too strong and for which the concept of strong stability is appropriate. This book provides a solid mathematical framework for a structured approach to strongly stabilizable systems through integration of fundamental theory, physical applications and numerical results. The author incudes a mathematical framework for studying PDE models of large flexible structures, an important class of applications. The authors structured approach focuses on two themes: the development of system theoretic results for strongly stable systems, and the formulation of these results for a class of dissipative systems with collocated actuators and sensors. The tools set forth in this book extend the scope of applicability of PDE control techniques, including the important aspect of numerical approximation. Most importantly, the author justifies all theory by providing physical examples for which the theory is relevant. The book encompasses basic system theoretic notions, such as stability, stabilizability, detectability, coprime factorizations, and control related topics like Riccati equations, LQ optimal control, robust stabilization, nonlinear perturbations and numerical approximation.

Necessary and sufficient conditions for strong stability of distributed parameter systems

In this paper we propose definitions for strong stabilizability and strong detectability of infinite-dimensional control systems. We show that these definitions are appropriate by showing that they can be used to give necessary and sufficient conditions for the strong stability of a system in terms of its input-output stability. As an application, we discuss the strong stability of the feedback interconnection of two strongly stabilizable and strongly detectable systems.

Visual hashing of digital video : applications and techniques

This paper present the concept of robust video hashing as a tool for video identification. We present considerations and a technique for (i) extracting essential perceptual features from a moving image sequences and (ii) for identifying any sufficiently long unknown video segment by efficiently matching the hash value of the short segment with a large database of pre-computed hash values.

The Nehari problem for nonexponentially stable systems

The Nehari problem and its suboptimal extension are solved under the assumption that the system Σ(A, B, C) has bounded controllability and observability maps, an L2-impulse response and a transfer matrix that is bounded and holomorphic on the right half-plane. Exponential stability of the semigroup is not assumed and the Hankel operator is not compact. The new contribution is an explicit parameterization of all solutions given in terms of the system parametersA, B, C.

The Popov criterion for strongly stable distributed parameter systems

In this article we generalize the Popov criterion to the class of strongly stable infinite-dimensional linear systems; the semigroup is strongly stable and the input to state, state to output and input to output maps are all bounded on the infinite-time interval. One application is to show that integral control can be used to track constant reference signals for positive-real strongly stable systems in the presence of sectorial non-linearities. A second application is to show the robustness of asymptotic stability of positive-real strongly stable systems to a large class of non-linear perturbations. Systems satisfying the assumptions in this paper include dissipative systems with collocated actuators and sensors.

An Approximation Theory for Strongly Stabilizing Solutions to the Operator LQ Riccati Equation

The linear-quadratic (LQ) control problem is considered for a class of infinite-dimensional systems with bounded input and output operators, that are not exponentially stabilizable, but only strongly stabilizable. A sufficient condition for the existence of a minimizing control and of a stabilizing solution to the associated LQ Riccati equation is given. The main contribution of this paper is the convergence of the stabilizing solutions of a sequence of finite-dimensional Riccati equations to the strongly stabilizing solution of the infinite-dimensional Riccati equation. The result is applied to a model of propagation of sound waves in a one-dimensional wave-guide.

Rate Adaptation in Time Varying Channels using Acknowledgement Feedback

Throughput maximization in a packet switched wireless communication system is considered in this paper. The channel variation is accounted for by modeling the channel as a finite state Markov channel. To maximize the throughput, rate adaptation is performed based on a single bit acknowledgement feedback. In general, when the window of packets considered is large, obtaining a global optimal rate adaptation solution is computationally difficult. A successive rate adaptation is derived which we show is necessarily sub-optimal by relating it to the optimal solution. This is complemented by a particle filter that is used to estimate the a posterior distribution of the channel. Numerical results illustrate that significant throughput can be recovered for slowly varying channels