We present a non-conformal metric that generalizes the geodesic active contours approach for image segmentation. The new metric is obtained by adding to the Euclidean metric an additional term that penalizes the misalignment of the curve with the image gradient and multiplying the resulting metric by a conformal factor that depends on the edge intensity. In this way, a closer fitting to the edge direction results. The provided experimental results address the computation of the geodesics of the new metric by applying a gradient descent to externally provided curves. The good performance of the proposed techniques is demonstrated in comparison with other active contours methods.

We present new algorithms for the recovery of the Euclidean structure from a projective calibration of a set of cameras with square pixels but otherwise arbitrarily varying intrinsic and extrinsic parameters. Our results, based on a novel geometric approach, include a closed-form solution for the case of three cameras and two known vanishing points and an efficient one-dimensional search algorithm for the case of four cameras and one known vanishing point. In addition, an algorithm for a reliable automatic detection of vanishing points on the images is presented. These techniques fit in a 3D reconstruction scheme oriented to urban scenes reconstruction. The satisfactory performance of the techniques is demonstrated with tests on synthetic and real data.

Given a projective reconstruction of a 3D scene, we address the problem of recovering the Euclidean structure of the scene in a recursive way. This leads to the application of Kalman filtering to the problem of camera autocalibration and to new algorithms for the autocalibration of cameras with varying parameters. This has benefits in saving memory and computational effort, and obtaining faster updates of the 3D Euclidean structure of the scene under consideration.

We present new results on the absolute line quadric (ALQ), the geometric object representing the set of lines that intersect the absolute conic. We include new techniques for the obtainment of the Euclidean structure that lead to an efficient algorithm for the autocalibration of cameras with varying parameters.

We provide a new technique for the Euclidean upgrading of a projective calibration for a set of ten or more cameras with known skew angle and aspect ratio and arbitrary varying focal length and principal point. The proposed algorithm, which is purely linear and thus of very low computational cost and not suffering from initialization problems, is based on the geometric object given by the set of lines incident with the absolute conic. We include experiments, which show the good performance of the technique.

We propose a new algorithm for the real-time control of an inter-frame video coder operating with a variable rate channel such as wireless channels or the Internet. Using techniques of stochastic dynamic programming we obtain off-line optimal policies from stochastic models of the channel and coder which minimize the average expected distortion. The on-line complexity of our approach is only that required to identify the state of the system (source and channel). The state of the channel is obtained based on the ARQ error-control mechanism, and the source state is computed as complexity measurements on each incoming frame. Simulation results based on this new approach are provided and compared to other proposed rate-control strategies. They show how our model-based optimal policies outperform the other considered approaches keeping a negligible on-line computational cost. This result is very interesting when considering an alternative to traditional costly solutions based on deterministic dynamic programming.

Traditionally, building 3D reconstructions of large scenarios such as a museum or historical site has been costly, time consuming and required the contribution of expert personnel. Usually the results showed an artificial look and had little interactivity. However, newly developed technologies in the areas of video analysis, camera calibration and texture fusion allow us to think in a much more satisfying scenario where the user with the only aid of a domestic video camera is able to acquire all the information it is required to construct the 3D model of the desired environment in an easy and comfortable manner. In this paper, the results obtained in the EC funded project VISIRE are presented. VISIRE attempts to construct photorealistic 3D models of large scenarios using as input multiple freehand video sequences. Once acquired, the computer vision software processes the video information off-line in order to obtain the 3D mesh together with the textures required to obtain a 3D model highly resembling the original.

We introduce a new approach to deal with the transmission of real-time video over wireless channels, based on a priori stochastic models for both source and channel. This new problem formulation captures in a natural way the stochastic nature of the channel as well as the uncertainty regarding the properties of the video sequence. Our formulation leads to an optimal control problem that can be solved off-line, employing standard stochastic dynamic programming techniques. The outcome of this optimization is an off-line control policy that is optimal in the sense of minimizing the average coding distortion. The on-line computational cost of the new approach is thus very low: all that is required during run-time is to identify the state of the system (source and channel). Unlike other optimization-based rate control techniques, which require a search for the optimal operating point, the operating points here for each allowable state of the system have been precalculated. We consider wireless packet-based transmission with Automatic Repeat reQuest (ARQ) error control. While a standard model has been adopted to characterize the channel behavior, a new model based on the concept of coding complexity has been devised in order to characterize the video source. Simulation results based on this new approach are provided and compared to other proposed rate-control strategies. They show how the use of model-based optimal policies has negligible on-line computational cost while providing a transmission quality comparable to that achieved with more costly deterministic dynamic programming techniques, and significantly better than for simpler algorithms that do not explicitly take into account the channel state.

We study the transmission of real-time video over wireless channels, proposing a formulation of the problem that includes a priori stochastic models for both source and channel. Using techniques of stochastic dynamic programming, we obtain offline optimal policies for each system state that minimize the average expected frame distortion. The online complexity of our approach is only that required to identify the state of the system (source and channel). The state of the channel is obtained based on the ARQ error-control mechanism, and the source state is computed as a complexity measurement on each incoming frame. Simulation results based on this new approach are provided and compared to other proposed rate-control strategies. They show how our model-based optimal policies require negligible on-line computational cost while providing a transmission quality comparable to that achieved with more complex deterministic dynamic programming techniques, and better than for simpler algorithms such as TMN.

The application of SADWT (shape adaptive discrete wavelet transform) has been widely proposed for object-oriented video coding, making it possible to transform and code the arbitrarily-shaped regions obtained by a segmentation of the scene content (which are usually objects in the sense of being a visually observable part of the image context). We present an application which is not restricted to objects but is meant to deal with any kind of region that is desired to be treated in a special way according to the coding objectives. Hereby, the main idea is to achieve a more efficient use of the available bits on areas with high prediction error (important for very low bit-rate coding) or skin-coloured areas (important for video telephony or conferencing). The coding of these areas can be independent, i.e. without taking into account the rest of the image, or could be controlled by multi-object bit distribution algorithms. Promising results for subjective quality tests have already been obtained at fixed bit rates with fixed and variable allocation strategies and our 2D irregular mesh based video coder, as well as for very-low bit-rate coding.

In previous years, an interest has developed in the coded representations of video signals allowing independent manipulation of semantically independent elements (objects). Along these lines, the ISO standard MPEG-4 enhances the traditional concept of the video sequence to convert it into a synchronized set of visual objects organized in a flexible way. The real-time generation of a bitstream according to this new paradigm, and suitable for its transmission through either fixed- or variable-rate channels, results in a challenging new bit allocation and rate control problem, which has to satisfy complex application requirements. This paper formalizes this new issue by focusing on the design of rate control systems for real-time applications. The proposed approach relies on the modelization of the source and the optimization of a cost criterion based on signal quality parameters. Different cost criteria are provided, corresponding to a set of relevant definitions of the object priority concept. Algorithms are introduced to minimize the average distortion of the objects, to guarantee desired qualities to the most relevant ones, and to keep constant ratios among the object qualities. The techniques have been applied to a coder implementing the MPEG-4 video verification model, showing good properties in terms of achievement of the control objectives.

The problem of controlling a video coder in order to adapt its variable output bit-rate to the input requirements of the communication channel has received a lot of attention. While in the reported work the performance of the control system is mainly measured in terms of the resulting average coding distortion and its degree of variability, only the minimization of the first has received enough attention as a case for systematic optimization, while the joint minimization of the two terms has only received a heuristic treatment. This paper investigates the compromise between average distortion and distortion variability within the frame of the model-based optimal control for overflow-safe operation of the coder. For this purpose, the systematic obtaining of control policies which optimize a general measure of the dynamical performance of the system is addressed as an extension of the classical formulation of the buffer control problem. By obtaining optimal solutions for different parts of the general performance measure, the compromise between the average value of the distortion and its average variability is made explicit and its qualitative aspects analyzed. Results are provided for an ITU-standard hybrid video coder.

Transmission of variable bit-rate encoded video over either constant or variable bit-rate communication channels imposes restrictions on the shape of the bit generation process in the encoder. In order that these restrictions can be met, a coder-network interface system has be to included consisting of a buffer and a coder controller device. In this paper we show how the availability of appropriate statistical models of the behavior of the source-coder system allows the formalization of the problem of the controller design as a stochastic optimal control problem, which can be solved by direct application of dynamic programming algorithms. Focusing the problem in the adaptation of a hybrid DCT coder to a fixed bit-rate channel, examples of the three stages of the process (source-coder modelization, problem definition, and optimal policy computation) are provided.

The different nature of the TV and HDTV signals, which hold dissimilar features from both the statistical and perceptual points of view, implies that the same behavior cannot be expected from the encoding procedure. Here, it is shown a comparison of the performances of a Hybrid DCT bit rate compression system when applied to information of each type. This study is carried out taking as a basis the statistics of the output data which result from the processing of corresponding HDTV and TV sequences, and it is described by several sets of data, relevant at different stages of the encoding process, such as DCT-domain energy distributions, quality versus bit rate curves, and final symbol statistics.