A factorization-based approach for articulated nonrigid shape, motion and kinematic chain recovery from video

Recovering articulated shape and motion, especially human body motion, from video is a challenging problem with a wide range of applications in medical study, sport analysis and animation, etc. Previous work on articulated motion recovery generally requires prior knowledge of the kinematic chain and usually does not concern the recovery of the articulated shape. The non-rigidity of some articulated part, e.g. human body motion with nonrigid facial motion, is completely ignored. We propose a factorization-based approach to recover the shape, motion and kinematic chain of an articulated object with nonrigid parts altogether directly from video sequences under a unified framework. The proposed approach is based on our modeling of the articulated non-rigid motion as a set of intersecting motion subspaces. A motion subspace is the linear subspace of the trajectories of an object. It can model a rigid or non-rigid motion. The intersection of two motion subspaces of linked parts models the motion of an articulated joint or axis. Our approach consists of algorithms for motion segmentation, kinematic chain building, and shape recovery. It handles outliers and can be automated. We test our approach through synthetic and real experiments and demonstrate how to recover articulated structure with non-rigid parts via a single-view camera without prior knowledge of its kinematic chain.     

Camera Control in Computer Graphics

Recent progress in modelling, animation and rendering means that rich, high fidelity virtual worlds are found in many interactive graphics applications. However, the viewer's experience of a 3D world is dependent on the nature of the virtual cinematography, in particular, the camera position, orientation and motion in relation to the elements of the scene and the action. Camera control encompasses viewpoint computation, motion planning and editing. We present a range of computer graphics applications and draw on insights from cinematographic practice in identifying their different requirements with regard to camera control. The nature of the camera control problem varies depending on these requirements, which range from augmented manual control (semi‐automatic) in interactive applications, to fully automated approaches. We review the full range of solution techniques from constraint‐based to optimization‐based approaches, and conclude with an examination of occlusion management and expressiveness in the context of declarative approaches to camera control.     

Delineating Boundaries for Imprecise Regions

In geographic information retrieval, queries often name geographic regions that do not have a well-defined boundary, such as “Southern France.” We provide two algorithmic approaches to the problem of computing reasonable boundaries of such regions based on data points that have evidence indicating that they lie either inside or outside the region. Our problem formulation leads to a number of subproblems related to red-blue point separation and minimum-perimeter polygons, many of which we solve algorithmically. We give experimental results from our implementation and a comparison of the two approaches. This research is supported by the EU-IST Project No. IST-2001-35047 (SPIRIT) and by grant WO 758/4-2 of the German Research Foundation (DFG).     

Effects of the metacognitive computer-tool met.a.ware on the web search of laypersons

Today, laypersons often consult the Internet to inform themselves about health-related issues. However, the competent use of these often complex and heterogeneous information provisions cannot be taken for granted, because many Internet users are lacking the necessary metacognitive prerequisites. Therefore, we developed the metacognitive computer-tool met.a.ware, which supports laypersons’ Internet research for medical information by the means of metacognitive prompting and ontological classification. In an experimental investigation of met.a.ware a total of 118 participants with little medical knowledge were asked to conduct an Internet research on a medical topic. Participants were randomly assigned to four experimental groups that worked with met.a.ware and either received evaluation prompts, monitoring prompts, both types of prompts, or no prompts. All experimental conditions were additionally provided with ontological classification. One control group took paper and pencil notes. A further control group took notes using a blank text window. Results showed that laypersons receiving evaluation prompts outperformed controls in terms of knowledge about sources and produced more arguments commenting on the source of information in an essay task. In addition, laypersons receiving monitoring prompts acquired significantly more knowledge about facts, but did not perform better on a comprehension test than the controls. The availability of ontological categories helped to structure the notes laypersons in the conditions working with ontological classification took during Internet research. Analyses of the notes further demonstrated that the availability of ontological categories guided information search in direction of the selected categories. It is concluded, that met.a.ware is an effective tool that supports laypersons’ Internet research.     

Sequential fixed-point ICA based on mutual information minimization

A new gradient technique is introduced for linear independent component analysis (ICA) based on the Edgeworth expansion of mutual information, for which the algorithm operates sequentially using fixed-point iterations. In order to address the adverse effect of outliers, a robust version of the Edgeworth expansion is adopted, in terms of robust cumulants, and robust derivatives of the Hermite polynomials are used. Also, a new constrained version of ICA is introduced, based on goal programming of mutual information objectives, which is applied to the extraction of the antepartum fetal electrocardiogram from multielectrode cutaneous recordings on the mother's thorax and abdomen.     

Correction of color information of a 3D model using a range intensity image

Most active optical range sensors record, simultaneously with the range image, the amount of light reflected at each measured surface location: this information forms what is called a range intensity image, also known as a reflectance image. This paper proposes a method that uses this type of image for the correction of the color information of a textured 3D model. This color information is usually obtained from color images acquired using a digital camera. The lighting condition for the color images are usually not controlled, thus this color information may not be accurate. On the other hand, the illumination condition for the range intensity image is known since it is obtained from a controlled lighting and observation configuration, as required for the purpose of active optical range measurement. The paper describes a method for combining the two sources of information, towards the goal of compensating for a reference range intensity image is first obtained by considering factors such as sensor properties, or distance and relative surface orientation of the measured surface. The color image of the corresponding surface portion is then corrected using this reference range intensity image. A B-spline interpolation technique is applied to reduce the noise of range intensity images. Finally, a method for the estimation of the illumination color is applied to compensate for the light source color. Experiments show the effectiveness of the correction method using range intensity images.     

A strategic classification support system for brownfield redevelopment

Brownfield redevelopment (BR) is an ongoing issue for governments, communities, and consultants around the world. It is also an increasingly popular research topic in several academic fields. Strategic decision support that is now available for BR is surveyed and assessed. Then a dominance-based rough-set approach is developed and used to classify cities facing BR issues according to the level of two characteristics, BR effectiveness and BR future needs. The data for the classification are based on the widely available results of a survey of US cities. The unique features of the method are its reduced requirement for preference information, its ability to handle missing information effectively, and the easily understood linguistic decision rules that it generates, based on a training classification provided by experts. The resulting classification should be a valuable aid to cities and governments as they plan their BR projects and budgets.     

Designing an extensible architecture for Personalized Ambient Information

Ambient displays provide us with information in the background of our awareness. However, as each user has individual wishes and needs of how, which and when information is presented, the acceptance of ambient displays is low.In this paper we introduce an extensible architecture for personalized ambient information.We employ a notification system to extend the capability of a fixture to display more than one variable. Multiple variables can be updated by multiple information providers. Thereby, our architecture covers a broader spectrum of notifications from alarms to ambient information.We evaluate our concept within a dual-task experiment in comparison to preset notifications. The results show a level of self-interruption which is significantly lower than using preset notifications. Therefore our approach outperforms preset notifications and moves ambient displays closer to secondary displays in human–computer interaction.     

A survey of RFID privacy approaches

A bewildering number of proposals have offered solutions to the privacy problems inherent in RFID communication. This article tries to give an overview of the currently discussed approaches and their attributes.

Wide band resonant ultrasound spectroscopy of spheroidal modes for high accuracy estimation of Poisson coefficient of balls

An original inversion method specifically adapted to the estimation of Poisson coefficient of balls by using their resonance spectra is described. From the study of their elastic vibrations, it is possible to accurately characterize the balls. The proposed methodology can create both spheroidal modes in the balls and detect such vibrations over a large frequency range. Experimentally, by using both an ultrasonic probe for the emission (piezoelectric transducer) and a heterodyne optic probe for the reception (interferometer), it was possible to take spectroscopic measurements of spheroidal vibrations over a large frequency range (100 kHz-45 MHz) in a continuous regime. This method, which uses ratios between wave resonance frequencies, allows the Poisson coefficient to be determined independently of Young's modulus and the ball's radius and density. This has the advantage of providing highly accurate estimations of Poisson coefficient (+/-4.3 x 10(-4)) over a wide frequency range.