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Semantic segmentation and object detection are nowadays dominated by methods operating on regions obtained as a result of a bottom-up grouping process (segmentation) but use feature extractors developed for recognition on fixed-form (e.g. rectangular) patches, with full images as a special case. This is most likely suboptimal. In this paper we focus on feature extraction and description over free-
This paper describes a new method of finding thin, elongated structures in images and volumes. We use shortest paths to minimize very general functionals of higher-order curve properties, such as curvature and torsion. Our method uses line graphs to find the optimal path on a given discretization, often in the order of seconds on a single computer. The curves are then refined using local optimizat
Many embedded systems comprise several controllers sharing available resources. It is well known that such resource sharing leads to complex timing behavior that degrades the quality of control, and more importantly, can jeopardize stability in the worst-case, if not properly taken into account during design. Although stability of the control applications is absolutely essential, a design flow dri
It has recently been shown that several classical open problems in linear system theory, such as optimization of decentralized output feedback controllers, can be readily solved for positive systems using linear programming. In particular, optimal solutions can be verified for large-scale systems using computations that scale linearly with the number of interconnections. Hence two fundamental adva
In high throughput applications, such as in multimedia, it is preferable to fully utilize computing resources, even at the price of some (bounded) delay. However, in real-time systems, where the maximum admissible delay is modeled by a deadline, most of the theory is developed with the assumption of a task deadline smaller than or equal to the task period. The reason of this limitation is in the i
We propose an energy-based framework for approximating surfaces from a cloud of point measurements corrupted by noise and outliers. Our energy assigns a tangent plane to each (noisy) data point by minimizing the squared distances to the points and the irregularity of the surface implicitly defined by the tangent planes. In order to avoid the well-known "shrinking" bias associated with first-order
A fundamental problem in robotics is generating the motion for a task. How to translate a task to motion or a series of movements is a non-trivial problem. The complexity of the task, the structure of the robot, and the desired performance determine the sequence of movements, the path, and the course of motion as a function of time, namely the trajectory. As we discuss in this thesis, a trajectory
In this paper we introduce a new algorithm for seismic imaging based on the flow out of Gaussian wave packets. We follow the standard strategy of decomposing data into wave packets and flowing them out along rays to approximate the downward wavefield extrapolation, and finally applying an imaging condition. We revisit each computational step to gain efficiency. Furthermore, we develop procedure fo
The purpose of this technical note is to present a new formula to compute the incipient breaking wave properties based on a simplified solution of the wave energy flux conservation equation combined with Snell's law. The execution time and calculated results of the new formula were compared with those of the iterative method which is commonly used in coastal engineering calculations, including in
Industrial robots are fast and accurate when working with known objects at precise locations in well-structured manufacturing environments, as done in the classical automation setting. In one sense, limited use of sensors leaves robots blind and numb, unaware of what is happening in their surroundings. Whereas equipping a system with sensors has the potential to add new functionality and increase
Current trends in industrial automation are the need for customizable production, vertical integration, more advanced sensors and actuators, and shorter time to market. The currently used control systems and languages for control were developed with a more static production in mind. More flexible languages and tools are needed to get a more flexible production. The flexible graphical programming l
In automotive systems, some of the engine control tasks are triggered by specific crankshaft rotation angles and are designed to adapt their functionality based on the angular velocity of the engine. This paper proposes a new task model for specifying such a type of real-time activities and presents an approach for analyzing the system feasibility under dynamic scheduling for different scenarios.
Particle number size distributions at various field sites are used to identify atmospheric new-particle formation (NPF) event days. However, the spatial distribution of regionally extensive events is unknown. To remedy this situation, the NanoMap method has been developed to enable the estimation of where NPF occurs within 500 km from any field station using as input size distribution and meteorol
In this article we consider how the operator of an electric power system should activate bids on the regulating power market in order to minimize the expected operation cost. Important characteristics of the problem are reaction times of actors on the regulating market and ramp-rates for production changes in power plants. Neglecting these will in general lead to major underestimation of the opera
Most atmospheric motions of different spatial scales and precipitation are closely related to phase transitions in clouds. The continuously increasing resolution of large-scale and mesoscale atmospheric models makes it feasible to treat the evolution of individual clouds. The explicit treatment of clouds requires the simulation of cloud microphysics. Two main approaches describing cloud microphysi
This paper presents a novel online approach of merging multiple different predictors of time-varying dynamics into a single optimized prediction. Different predictors are merged by recursive weighting into a single prediction using regularized optimization. The approach is evaluated on two different cases of data with shifting dynamics; one example of prediction using several approximate models of
Systems based on bag-of-words models from image features collected at maxima of sparse interest point operators have been used successfully for both computer visual object and action recognition tasks. While the sparse, interest-point based approach to recognition is not inconsistent with visual processing in biological systems that operate in 'saccade and fixate' regimes, the methodology and emph
Model predictive control (MPC) is applied to a physical pendulum system consisting of a pendulum and a cart. The objective of the MPC controller is to steer the system towards precomputed, time-optimal feedforward trajectories that move the system from one stationary point to another. The sample time of the controller sets hard limitations on the execution time of the optimization algorithm in the
