Characterization for High Dynamic Range Imaging

In this paper we present a new practical camera characterization technique to improve color accuracy in high dynamic range (HDR) imaging. Camera characterization refers to the process of mapping device‐dependent signals, such as digital camera RAW images, into a well‐defined color space. This is a well‐understood process for low dynamic range (LDR) imaging and is part of most digital cameras — usually mapping from the raw camera signal to the sRGB or Adobe RGB color space. This paper presents an efficient and accurate characterization method for high dynamic range imaging that extends previous methods originally designed for LDR imaging. We demonstrate that our characterization method is very accurate even in unknown illumination conditions, effectively turning a digital camera into a measurement device that measures physically accurate radiance values — both in terms of luminance and color — rivaling more expensive measurement instruments.     

Application of reinforcement learning to the game of Othello

Operations research and management science are often confronted with sequential decision making problems with large state spaces. Standard methods that are used for solving such complex problems are associated with some difficulties. As we discuss in this article, these methods are plagued by the so-called curse of dimensionality and the curse of modelling. In this article, we discuss reinforcement learning, a machine learning technique for solving sequential decision making problems with large state spaces. We describe how reinforcement learning can be combined with a function approximation method to avoid both the curse of dimensionality and the curse of modelling. To illustrate the usefulness of this approach, we apply it to a problem with a huge state space—learning to play the game of Othello. We describe experiments in which reinforcement learning agents learn to play the game of Othello without the use of any knowledge provided by human experts. It turns out that the reinforcement learning agents learn to play the game of Othello better than players that use basic strategies.     

Efficient tracking of the dominant eigenspace of a normalized kernel matrix

Various machine learning problems rely on kernel-based methods. The power of these methods resides in the ability to solve highly nonlinear problems by reformulating them in a linear context. The dominant eigenspace of a (normalized) kernel matrix is often required. Unfortunately, the computational requirements of the existing kernel methods are such that the applicability is restricted to relatively small data sets. This letter therefore focuses on a kernel-based method for large data sets. More specifically, a numerically stable tracking algorithm for the dominant eigenspace of a normalized kernel matrix is proposed, which proceeds by an updating (the addition of a new data point) followed by a downdating (the exclusion of an old data point) of the kernel matrix. Testing the algorithm on some representative case studies reveals that a very good approximation of the dominant eigenspace is obtained, while only a minimal amount of operations and memory space per iteration step is required.     

Motion Planning for Haptic Guidance

Haptic devices allow a user to feel either reaction forces from virtual interactions or reaction forces reflected from a remote site during a bilateral teleoperation task. Also, guiding forces can be exerted to train the user in the performance of a virtual task or to assist him/her to safely teleoperate a robot. The generation of guiding forces relies on the existence of a motion plan that provides the direction to be followed to reach the goal from any free configuration of the configuration space (-space). This paper proposes a method to obtain such a plan that interleaves a sampling-based exploration of -space with an efficient computation of harmonic functions. A deterministic sampling sequence (with a bias based on harmonic function values) is used to obtain a hierarchical cell decomposition model of -space. A harmonic function is iteratively computed over the partially known model using a novel approach. The harmonic function is the navigation function used as motion plan. The approach has been implemented in a planner (called the Kautham planner) that, given an initial and a goal configuration, provides: (a) a channel of cells connecting the cell that contains the initial configuration with the cell that contains the goal configuration; (b) two harmonic functions over the whole -space, one that guides motions towards the channel and another that guides motions within the channel towards the goal; and (c) a path computed over a roadmap built with the free samples of the channel. The harmonic functions and the solution path are then used to generate the guiding forces for the haptic device. The planning approach is illustrated with examples on 2D and 3D workspaces. This work was partially supported by the CICYT projects DPI2005-00112 and DPI2007-63665.     

Topological Repairing of 3D Digital Images

We present here a new randomized algorithm for repairing the topology of objects represented by 3D binary digital images. By “repairing the topology”, we mean a systematic way of modifying a given binary image in order to produce a similar binary image which is guaranteed to be well-composed. A 3D binary digital image is said to be well-composed if, and only if, the square faces shared by background and foreground voxels form a 2D manifold. Well-composed images enjoy some special properties which can make such images very desirable in practical applications. For instance, well-known algorithms for extracting surfaces from and thinning binary images can be simplified and optimized for speed if the input image is assumed to be well-composed. Furthermore, some algorithms for computing surface curvature and extracting adaptive triangulated surfaces, directly from the binary data, can only be applied to well-composed images. Finally, we introduce an extension of the aforementioned algorithm to repairing 3D digital multivalued images. Such an algorithm finds application in repairing segmented images resulting from multi-object segmentations of other 3D digital multivalued images.

The Structure of Visual Spaces

The “visual space” of an optical observer situated at a single, fixed viewpoint is necessarily very ambiguous. Although the structure of the “visual field” (the lateral dimensions, i.e., the “image”) is well defined, the “depth” dimension has to be inferred from the image on the basis of “monocular depth cues” such as occlusion, shading, etc. Such cues are in no way “given”, but are guesses on the basis of prior knowledge about the generic structure of the world and the laws of optics. Thus such a guess is like a hallucination that is used to tentatively interpret image structures as depth cues. The guesses are successful if they lead to a coherent interpretation. Such “controlled hallucination” (in psychological terminology) is similar to the “analysis by synthesis” of computer vision. Although highly ambiguous, visual spaces do have geometrical structure. The group of ambiguities left open by the cues (e.g., the well known bas-relief ambiguity in the case of shape from shading) may be interpreted as the group of congruences (proper motions) of the space. The general structure of visual spaces for different visual fields is explored in the paper. Applications include improved viewing systems for optical man-machine interfaces.     

Shared WiFi-Communities – User Generated Infrastructure am Beispiel von FON

Shared WiFi-Communities emerge when users share their private Wireless Fidelity with others and in return get free internet access via community members’ internet connection. Supply of wireless capacity and demand for WLAN usually are coordinated by a central authority therewith users can find specific hosts within the community. Initial players that conduct commercial WiFi-Communities established their position in the market. The international market leader with 170,000 hotspots worldwide is FON. The commercial success of shared WiFi-communities (e.g. FON) depends on the adoption of a special router or modifications of the existing WLAN-infrastructure. More importantly it is essential that users permanently offer broadband capacity to the community. Only then net effects can durably generate enhanced usage benefits. A survey of 268 German FON users reveals that the community shows a high level of cohesion. Users barely vary from the default setting concerning shared bandwidth of the router. Additionally most interviewees offer their WLAN 24 hours a day. Despite the possibility of earning money with the wireless capacity most users do not offer bandwidth with a purely economic ambition. Although the market potential of shared WiFi communities appears tremendous legal obstructions and technical restraints exacerbate penetration.     

Decentralised control of chromatographic simulated moving bed processes based on wave front reconstruction

The behaviour of chromatographic simulated moving bed processes is described by the movement of concentration profiles through a circle of separation columns. A closed-loop control manipulates the profiles in order to meet demands concerning specified product purity and disturbance attenuation. If steep wave fronts of the concentration profiles occur, the controlled variables undergo fast changes in case of a transient of the process. In this case, a reconstruction of the wave fronts is necessary for a successful control.A simple and effective decentralised controller structure is proposed based on cascaded discrete-time PI controllers. On-line product purity measurements and the reconstructed wave fronts are used for control purposes. Two kinds of process models are used: a rigorous model for dynamic simulations, and strongly simplified plant models for the design of the wave front reconstruction and the controller. The latter models are identified based on experimental step tests with the reference plant and numerical simulations. The performance of the control system is evaluated by numerical simulations.     

Disjunctive databases for representing repairs

This paper addresses the problem of representing the set of repairs of a possibly inconsistent database by means of a disjunctive database. Specifically, the class of denial constraints is considered. We show that, given a database and a set of denial constraints, there exists a (unique) disjunctive database, called canonical, which represents the repairs of the database w.r.t. the constraints and is contained in any other disjunctive database with the same set of minimal models. We propose an algorithm for computing the canonical disjunctive database. Finally, we study the size of the canonical disjunctive database in the presence of functional dependencies for both subset-based repairs and cardinality-based repairs.     

A new,flexible and widely applicable software package for the simulation of one-dimensional moisture flow: SoWaM

Most one-dimensional soil moisture flow simulation models have restricted applicability due to (amongst other things): i) insufficient user flexibility; ii) a lack of user friendliness; iii) dependency on scale, temporal and/or spatial, and iv) fixed boundary conditions. Therefore, we developed a simple and highly flexible software package to simulate, visualize and analyze 1-D moisture flow in soils: SoWaM (Soil Water Model). The package has a modular setup and consists of a range of tools to visualize, analyze and compare input data and results. Soil hydraulic properties for each specified soil layer can be defined by either Van Genuchten parameters or cubical splines. Since the model does not impose limits on element size or time interval, it is possible to perform simulations in very high detail, both spatially and temporally. Furthermore, four different criteria for irrigation scheduling have been implemented. The SoWaM package provides an accurate, simple and highly flexible tool to simulate soil moisture flow and to evaluate the effects of various factors on soil water movement, such as timing and amount of irrigation, soil hydraulic properties and soil layering. Results of a case study are presented to illustrate model performance.