We present an approach for probabilistic contour prediction within the framework of an object tracking system. We combine level-set methods for image segmentation with optical flow estimations based on probability distribution functions (pdfs) calculated at each image position. Unlike most recent level-set methods that consider exclusively the sign of the level-set function to determine an object and its background, we introduce a novel interpretation of the value of the level-set function that reflects the confidence in the contour. To this end, in a sequence of consecutive images, the contour of an object is transformed according to the optical flow estimation and used as the initial object hypothesis in the following image. The values of the initial level-set function are set according to the optical flow pdfs and thus provide an opportunity to incorporate the uncertainties of the optical flow estimation in the object contour prediction.
Hemispheric EEG slow-potential asymmetry (SPA) during a one-dimensional horizontal tracking task was recorded over Oi, O2, C3 and C4 electrode positions. The time instants of tracking error occurrences (CXJT events) and their corrections (IN events) were used as synchronization events in selected EEG epochs. The central values (medians) of amplitudes in the averaged 500 ms EEG epochs were used for SPA description. Significant negative correlations between medians calculated for the time epochs prior to and after the events were found indicating a specific influence of these events on SPA. Prior IN events the left hemisphere (represented by Oi and C3 positions only) was more negative than the right one, while it was significantly more positive after the same type of events. An opposite relationship was suggested for OUT events.
The simultaneous problem of consensus and trajectory tracking of linear multi-agent systems is considered in this paper, where the dynamics of each agent is represented by a single-input single-output linear system. In order to solve this problem, a distributed control strategy is proposed in this work, where the trajectory and the formation of the agents are achieved asymptotically even in the presence of switching communication topologies and smooth formation changes, and ensuring the closed-loop stability of the multi-agent system. Moreover, the structure and dimension of the representation of the agent dynamics are not restricted to be the same, as usually assumed in the literature. A simulation example is provided in order to illustrate the main results.
The intenzity of illumination of a solar panel depends on the angle between its normal and the direction of the solar beam and it can be, consequently, enhanced for the panel tracked towards the sun. The aim of the paper is to compare the intensity of illumination of the fixed (non-tracking) panel and illumination of the panel with one or two tracking axes. The annual irradiation and irradiation in individual months was determined using the coefficient of contamination Z = 4 characterizing the atmosphere in towns. The data of the sun elevation and azimuth during one year for the latitude 50° N were utilized for the calculation. and Intenzita ozáření slunečního panelu závisí na úhlu, který svírá jeho normála se směrem slunečních paprsků a může se proto zvýšit, bude-li se panel natáčet za sluncem. Cílem této práce je porovnat intenzitu ozáření pevného (nenatáčeného) panelu a panelu natáčeného za sluncem kolem jedné, případně dvou os. Byla určena iradiace panelu za celý rok i pro jednotlivé měsíce při koeficientu znečištění atmosféry Z = 4, který charakterizuje atmosféru ve městech. Pro výpočet byla využita data výšky slunce nad obzorem a azimutu v průběhu roku pro 50. stupeň severní šířky.
In this work, an alternative solution to the tracking problem for a SISO nonlinear dynamical system exhibiting points of singularity is given. An inversion-based controller is synthesized using the Fliess generalized observability canonical form associated to the system. This form depends on the input and its derivatives. For this purpose, a robust exact differentiator is used for estimating the control derivatives signals with the aim of defining a control law depending on such control derivative estimates and on the system state variables. This control law is such that, when applied to the system, bounded tracking error near the singularities is guaranteed.