Abstract: An audio signal processing system includes one or more sensors for sensing audio signals. A module for computing audio signal segments of coherent signal elements, and at least one compressing module for computing a compressed representation of audio features of each audio signal segment are also included. The system also has a module for storing audio proto objects, which are data objects comprising the compressed representation and time information of the associated audio signal segment.

Abstract: One embodiment of the present invention is a method for optimizing a parameter set comprising object parameters, the method comprising the steps of: (a) creating an initial population of a plurality of individual parameter sets, the parameter sets comprising object parameters describing a model, structure, shape, design or process to be optimized and setting the initial population as a current parent population; (b) for each individual parameter set in a parent population mutating the parameters and optionally recombining the parameters to create an offspring population of individual parameter sets, wherein the strength of an individual object parameter mutation is enlarged by a noise contribution to enhance the robustness of the optimization; (c) evaluating a quality of each individual in the offspring population; (d) selecting individuals of the offspring population to be the next parent generation; and (e) repeating steps (b) through (d) until a termination criterion is reached.

Abstract: Efficiently simulating an Amari dynamics of a neural field (a), the Amari dynamics being specified by the equation (1) where a(x,t) is the state of the neural field (a), represented in a spatial domain (SR) using coordinates x,t, i(x,i) is a function stating the input to the neural field at time t, f[.] is a bounded monotonic transfer function having values between 0 and 1, F(x) is an interaction kernel, s specifies the time scale on which the neural field (a) changes and h is a constant specifying the global excitation or inhibition of the neural field (a). A method for simulating an Amari dynamics of a neural field (a), comprising the step of simulating an application of the transfer function (f) to the neural field (a). According to the invention, the step of simulating an application of the transfer function (f) comprises smoothing the neural field (a) by applying a smoothing operator (S).

Abstract: The present invention relates to a technique for detecting dynamic (i.e., moving) objects using sensor signals with 3D information and can be deployed e.g. in driver assistance systems.

Abstract: A system and method for combining the model-based and genetics-based methods are combined according to a convergence criterion. When the population is not converged, the genetics-based approach is used, and when the population is converged, the model-based method is used to generate offspring. The algorithm benefits from using a model-based offspring generation only when the population shows a certain degree of regularity, i.e., converged in a stochastic sense. In addition, a more sophisticated method to construct the stochastic part of the model can be used. Also a biased Gaussian noise (the mean of the noise is not zero), as well as a white Gaussian noise (the mean of the noise is zero) can be preferably used for the stochastic part of the model.

Abstract: Techniques are disclosed for sound source localization based on joint learning and evaluation of ITD and ILD representations that are measured in a complementary, correlation-based way using binaural time-frequency spectrums. According to one embodiment, from these measurements and learned representatives, which may, for example, be created by combinations of measurements from signals belonging to the same class, i.e., the same azimuthal location, probability distributions over frequency and class are computed. These probability distributions can be combined over cue and frequency using information-theoretic approaches to get a robust classification of the location and additionally a confidence measure for the quality of the classification result.

Abstract: One embodiment of the present invention provides a method for gathering information from an environment. In a first step, visual information is gathered from the environment. In a second step, information actively transmitted by objects in the environment is received. According to one embodiment, the information actively transmitted by objects in the environment is received wirelessly. In a third step, the visual information is combined with the received information in order to recognize objects.

Abstract: Techniques are provided for representation of designs using a basic design which is then modified by a transformation function. In free form deformation techniques the transformation function is defined by a spline function which transforms the space in which the design is defined into a second space where the new modified design is defined. During the design process the parameters of the spline function determine the parameters of the transformation function. While using Evolution Strategies, parameters of the spline function also determine the parameters the optimization algorithm works in. In order to adapt the transformation function optimally to the given problem and the necessary modification a mutation operator is proposed which allows introduction and deletion of control points. Instead of the standard mutation operator in evolution strategies this mutation operator works on the representation of the problem/design.

Abstract: Estimating the dynamic states of a real-world object over time using a camera, two dimensional (2D) image information and a combination of different measurements of the distance between the object and the camera. The 2D image information is used to track a 2D position of the object as well as its 2D size of the appearance and change in the 2D size of the appearance of the object. In addition, the distance between the object and the camera is obtained from one or more direct depth measurements. The 2D position, the 2D size, and the depth of the object are coupled to obtain an improved estimation of three dimensional (3D) position and 3D velocity of the object. The object tracking apparatus uses the improved estimation to track real-world objects. The object tracking apparatus may be used on a moving platform such as a robot or a car with mounted cameras for a dynamic visual scene analysis.

Abstract: A method for segregating a figure region from a background region in image sequences from dynamic visual scenes, comprising the steps of: (a) acquiring an image; (b) determining local motion estimations and confidences for each position of the image; (c) modifying a level-set function by moving and distorting the level-set function with the local motion estimations and smearing it based on the local motion confidences, to generate a predicted level set function that is geometrically in correspondence with the image and diffused at positions where the confidence of the motion estimation is low; (d) obtaining input features of the image by using a series of cues; (e) calculating a mask segregating the figure region from the background region of the image using the modified level-set function and the obtained input features; (f) extracting the figure region from the image; and repeating steps (a)-(f) until a termination criterion is satisfied.

Abstract: The invention relates to the control of an orienting/positioning system comprising comprising at least a sensor and an actuator for controlling an orienting and/or positioning action adapted to change an input space of the sensor. A first step evaluates pre-action output information of the sensor in order to detect a pre-action position of a manipulating device in the input space of the sensor. A second step decides on a targeted post-action position of the manipulating device in the input space of the sensor. A third step defines a command for the actuator by mapping any deviation of the pre-action position and the targeted post-action position in the input space of the sensor to actuator control coordinates using a predefined mapping function. A fourth step orients/positions the manipulating device according to the defined command in order to carry out the orienting/positioning action. A fifth step detects a real post-action position of the manipulating device in the input space of the sensor.

Abstract: A robot controller including a multitude of simultaneously functioning robot controller units. Each robot controller unit is adapted to receive an input signal, receive top-down information, execute an internal process or dynamics, store at least one representation, send top-down information, issue motor commands wherein each motor command has a priority. The robot controller selects one or several motor commands issued by one or several units based on their priority. Each robot controller unit may read representations stored in other robot controller units.

Abstract: A computer-implemented method of analyzing data representing the optimization of real-world designs of physical entities according to at least one criterion. Different modifications of the design are generated by a cyclic optimization algorithm. The design data is represented by unstructured triangular surface meshes. A displacement measure representing local differences between two design modifications of the different modifications is calculated. Performance difference between the two design modifications is calculated. The performance difference is represented by at least one criterion. Sensitivity information representing correlation between the displacement measure and the performance differences is outputted.

Abstract: A method for controlling a robot having at least one visual sensor. A target for a motion of the robot is defined. A motion control signal adapted for the robot reaching the target is calculated. A collision avoidance control signal based on the closest points of segments of the robot and a virtual object between the visual sensing means and the target is calculated. The motion control signal and the collision avoidance control signal are weighted and combined. The weight of the motion control signal is higher when a calculated collision risk is lower. The motion of the robot is controlled according to the combined signal so that no segment of the robot enters the space defined by the virtual object.

Abstract: A common problem in audio processing is that a useful signal is disturbed by one or more sinusoidal noises that should be suppressed. One embodiment of the invention provides a method of canceling a sinusoidal disturbance of unknown frequency in a disturbed useful signal. The method comprises the steps of estimating parameters of the sinusoidal disturbance including amplitude, phase and frequency; generating a reference signal on the basis of the estimated parameters; and subtracting the reference signal from the disturbed useful signal. According to one embodiment of the present invention, the estimation is performed by an Extended Kalman filter.

Abstract: A method for controlling a system or robot having at least one effector. An initial sequence of control points is computed. The system or the robot is evaluated by a global cost function that uses internal simulation based on the control points. The sequence of control points are updated based on the evaluation. The evaluation of the system or the robot and the updating of the sequence of control points are repeated until a given termination criterion is met.

Abstract: A method for optimizing a material structure. The method comprises the steps of encoding an initial design of the material structure to be optimized as a parameter set, subjecting the initial design to an optimization according to at least one preset criterion, using an evolutionary algorithm, terminating the optimization when a termination condition is met, and outputting data representing the optimized parameter set. The design of the material structure is encoded indirectly as a virtual DNA.

Abstract: The fundamental frequency of a harmonic signal is estimated by forming a fundamental frequency hypothesis (f0?). A comb filter is provided based on the fundamental frequency hypothesis. The harmonic signal is filtered using the comb filter. The fundamental frequency hypothesis is tested for each tooth in the comb filter. A signal indicating an estimated fundamental frequency of the provided harmonic signal may be outputted based on the testing.

Abstract: A robot is provided with a motion control unit that avoids collision between segments of the robot or between segments of the robot and other objects. The motion control unit of the robot comprises a distance computing module, a whole body control module, a collision avoidance module, and a blending control unit. The distance computing module calculates two closest points of different segments of the robot connected to each other via at least one joint or a segment of the robot and another object. The collision avoidance module is provided with the information about the two closest points. The blending control unit combines the weighted output control signals of the whole body control module and the collision avoidance control module. The weight of the whole body control output signal is higher when the risk of collision is lower. The weight of the collision avoidance control output signal is higher when the risk of collision is higher.

Abstract: The underlying invention generally relates to the field of Estimation of Distribution Algorithm, especially to optimization problems, including single-objective optimization and Multi-Objective Optimization. The proposed method for optimization comprises six steps. In a first step it provides an initial population or a data set with a plurality of members respectively represented by parameter sets. Then one or a plurality of fitness functions are applied to evaluate the quality of the members of the population. In a third step offspring of the population is generated by means of a stochastic model using information from all members of the population. One or a plurality of fitness functions are applied to evaluate the quality of the offspring with respect to the underlying problem of the optimization. In a fifth step offspring is selected. Lastly the method goes back to the third step until the quality reaches a threshold value.