Data Broadcasting and Interactive Television

This paper provides an overview of the digital television (DTV) data broadcast service and interactive service technologies that have been deployed over the last ten years. We show how these trials have led to the development of data protocol and software middleware specifications, worldwide. Particular attention is given to the series of standards established by the Advanced Television System Committee. Experimental deployments to both Personal Computer(PC) and Set-Top-Box (STB)/spl I.bar/receivers are considered, with an emphasis on the services that have introduced new business models for DTV operators.     

Signal transduction pathway modeling using sequences of chromatophore images

Extensive research is being done in order to use chromatophore cells as biosensors for various substances. In this paper, a link between the biological aspect of chromatophores and digital image/video processing techniques used for chromatophore characterization is established for this purpose. A model of the Gs--AC--PKA--granule motion-image feature signal transduction pathway is proposed, starting from the concentration of the input ligand and ending in the pigment area extracted from a microscope image. The model extends an existing system biology differential equation based model of the Gs--AC--PKA transduction pathway obtained from the Database of Quantitative Cellular Signaling (DQCS). Examples are presented to demonstrate the effectiveness of the proposed system model.     

Adaptive model-based motion estimation

A general discrete-time, adaptive, multidimensional framework is introduced for estimating the motion of one or several object features from their successive nonlinear projections on an image plane. The motion model consists of a set of linear difference equations with parameters estimated recursively from a nonlinear observation equation. The model dimensionality corresponds to that of the original, nonprojected motion space, thus allowing to compensate for variable projection characteristics such as paning and zooming of the camera. Extended recursive least-squares and linear-quadratic tracking algorithms are used to adaptively adjust the model parameters and minimize the errors of either smoothing, filtering or prediction of the object trajectories in the projection plane. Both algorithms are derived using a second order approximation of the projection nonlinearities. All the results presented here use a generalized vectorial notation suitable for motion estimation of any finite number of object features and various approximations of the nonlinear projection. The application of the model-based motion estimator for temporal decimation/interpolation in digital video sequence compression systems is presented.