Abstract: An improved optimization of a design, based on direct manipulations of the object points of a design where the number and modifications of control points is kept as minimal as possible while the targeted movement of object points is realized.

Abstract: A driver assistance system with an architecture of general use for applications related to driver assistance, passenger safety and comfort and communication with external systems, e.g.

Abstract: The invention proposes a method for object and object configuration tracking based on sensory input data, the method comprising the steps of: (1.1) Basic recruiting: Detecting interesting parts in sensory input data which are not yet covered by already tracked objects and incrementally initializing basic tracking models for these parts to continuously estimate their states, (1.2) Tracking model complexity adjustment: Testing, during runtime more complex and more simple prediction and/or measurement models on the tracked objects, and (1.3) Basic release: Releasing trackers from parts of the sensory data where the tracker prediction and measurement processes do not get sufficient sensory support for some time.

Abstract: A computer-implemented method for setting-up and operating a driver assistance system, the method comprising the steps of: visually sensing the environment of a vehicle, sensing at least one rate of change of a parameter representing a status of the car, which parameter can be influenced by a driver manipulating a man/machine interface of the vehicle, structuring information gathered by the visual sensing by classifying the at least one sensed rate of change in different categories of e, in order to find visual features associated to a certain category of sensed rate of change and thus associated with a certain behavior of the driver.

Abstract: A method for the computerized design of real-world object uses knowledge of already existing designs and their physical performance numbers. During the design process, a plurality of design variables are adapted, and the result of the design has improved physical performance numbers when converted into the real-world Object. The design process is decomposed in parallel streams of optimization modules, with each optimization module individually optimizing a group of interrelated design variables. The functional interrelation between design variables is evaluated using an interaction information representing the functional dependency between the design variables and the physical performance numbers.

Abstract: One embodiment of the present invention provides a method of determining an evidence value capturing whether two band-pass signals are harmonics of a common fundamental frequency. A further embodiment of the present invention evaluates the distance between significant points of a signal such as a sinusoidal signal. One embodiment of the present invention provides a method of determining whether two or more band-pass signals are harmonics of a fundamental frequency, comprising evaluating a first distance between a first set of two or more significant points of a first band-pass signal, evaluating a second distance between a second set of two or more significant points of a second band-pass signal, and comparing the first distance to the second distance to determine whether the first and second signals are harmonics of the fundamental frequency.

Abstract: Computer-assisted systems and methods for integrating aesthetic and functional design processes for real-world objects can include a computerized module for defining an aesthetic representation of a real-world object, and a computing module supplied with approximation model data of a CAE simulation module to calculate functional quality value(s) using a parametric description of the aesthetic representation as input. An interface can issue a physical signal to a user, with the physical signal communicating the quality value(s) to the user. A computerized module can change the parametric description of the aesthetic representation of the object in the aesthetic design process taking the obtained functional quality value into account.

Abstract: The invention relates to the field of automated processing of speech signals and particularly to a method for tracking the formant frequencies in a speech signal, comprising the steps of: obtaining an auditory image of the speech signal; sequentially estimating formant locations; segmenting the frequency range into sub-regions; smoothing the obtained component filtering distributions; and calculating exact formant locations.

Abstract: The invention proposes a method for detecting dynamic objects in the scene in a driver assistance system of a vehicle, comprising the steps of: feeding signals from sensors (internal sensors, 3D sensors, cameras) of the vehicle to the driver assistance system, generation of a surrounding model using 3D world positions based on the sensor signals and, combination of 3D Warping-based approaches and optical flow based approaches, whose gained novel key points are: a) Restriction of the search space of an optical flow method based on the computation results of the 3D warping method, b) Additionally, to a) also an optimal parameterization of the optical flow approach in terms of search direction, amplitude, etc., c) Refinement and verification of the detection results of one of the methods based on the computation results of the other method (if both approaches are running in parallel), storing the detected dynamic objects and their measured motion parameters for their use in, e.g.

Abstract: This invention is in the field of machine learning and neural associative memory. In particular the invention discloses a neural associative memory structure for storing and maintaining associations between memory address patterns and memory content patterns using a neural network, as well as methods for storing and retrieving such associations. Bayesian learning is applied to achieve non-linear learning.

Abstract: This invention is in the field of machine learning and neural associative memory. In particular the invention discloses a neural associative memory structure for storing and maintaining associations between memory address patterns and memory content patterns using a neural network, as well as methods for retrieving such associations. A method for a non-linear synaptic learning of discrete synapses is disclosed, and its application on neural networks is laid out.

Abstract: A method for generating a saliency map for a robot device having sensor means, the saliency map indicating to the robot device patterns in the input space of the sensor means which are important for carrying out a task; wherein the saliency map comprises a weighted contribution from a disparity saliency selection carried out on the basis of depth information gathered from the sensor means, such that a weighted priority is allocated to patterns being within a defined peripersonal space in the environment of the sensor means.

Abstract: The invention relates to a vision-based attention system, comprising: at least one vision sensor, at least one image processing module processing an output signal of the vision sensor in order to generate at least one two-dimensional feature map, a dorsal attention subsystem generating a first saliency map on the basis of the at least one feature map, the saliency map indicating a first focus of attention for the driver assistance system, a ventral attention subsystem, independent to the dorsal attention subsystem, for generating a second saliency map on the basis of at least one feature map, which can be the same as the one used for the dorsal attention system or a different one, the second saliency map indicating unexpected visual stimuli.

Abstract: A method for forming an associative computer memory comprises the step of forming an inhibitory memory matrix A?=?(Ap?A). According to the Wilshaw model constructed from a given set of address patterns and content patterns' and random matrix structure.

Abstract: A controller for the motion control of a robot, comprises: a target input interface for supplying the controller with information about a target to be reached, a predicting module predicting at least one future state of the controlled robot using an internal model of the robot, a planning module for planning future states of the robot, wherein the planning starts from a predicted state supplied from the predicting module, a reactive controller, for outputting motor commands in order to make the controlled robot reach a target, and a target arbitrator for selecting the target output by the predicting module or the output from the planning module.

Abstract: The invention relates to a method for processing video signals from a video sensor, in order to extract 3d shape information about objects represented in the video signals, the method comprising the following steps: providing a memory in which objects are stored in a 3d shape space, the shape space being an abstract feature space encoding the objects' 3d shape properties, and mapping a 2d video signal representation of an object in the shape space, the coordinates of the object in the shape space indicating the object's 3d shape.

Abstract: Iterative (nondeterministic) optimization of aerodynamic and hydrodynamic surface structures can be accomplished with a computer software program and a system using a combination of a variable encoding length optimization algorithm based on an evolution strategy and an experimental hardware set-up that allows to automatically change the surface properties of the applied material, starting with the overall shape and proceeding via more detailed modifications in local surface areas. The optimization of surface structures may be done with a computing device for calculating optimized parameters of at least one (virtual) surface structure, an experimental hardware set-up for measuring dynamic properties of a specific surface structure, and an interface for feeding calculated parameters from the computing device to the experimental set-up and for feeding measured results back to the computing device as quality values for the next cycle of the optimizing step.

Abstract: A robotic controller using schemata, the schemata being a set of parameterized sequences of motor commands in order to make a robot to achieve a set goal, the parameters of the sequences being gained from the state variables of the robotic controller, a robotic controller comprising an interface for supplying sensory input to the robotic controller. A schemata state memory (1) structure supplied with either input from a schemata recognition module (4) or input from an inverse model module (2) or combinations of them. An inverse model module (2) for generating motor commands based on state variables and stored schemata, a forward model module (3) for predicting state variables based on state variables and stored schemata, and a schemata recognition module (4) for selecting a schemata based on supplied state variables of the robot controlled by the robotic controller.

Abstract: Generally the background of the present invention is the field of artificial vision systems, i.e. systems having a visual sensing means (e.g. a video camera) and a following processing stage implemented using a computing unit. The processing stage outputs a representation of the visually analysed scene, which output can then be fed to control different actors, such as e.g. parts of a vehicle (automobile, plane, . . . ) or a robot, preferably an autonomous robot such as e.g. a humanoid robot.

Abstract: The invention proposes a method for imitation-learning of movements of a robot, wherein the robot performs the following steps: observing a movement of an entity in the robot's environment, recording the observed movement using a sensorial data stream and representing the recorded movement in a different task space representations, selecting a subset of the task space representations for the imitation learning and reproduction of the movement to be imitated.