Abstract: A computer-implemented method for generating control information for the remote control of an intervention device that is to be used during an intervention, for example a medical intervention, at an intervention location, wherein at least one first person is present at the intervention location and at least one second person is present at a location which differs from and is remote from the intervention location for the purpose of cooperation during the performance of the intervention, and control information provided by the second person is sent from the remote location to the intervention location by a communication connection, wherein use of the control information for controlling the intervention device is only enabled if a safeguarding signal, which indicates a monitoring activity of the first person and is output by a signaling device that may be activated by the first person, is present.

Abstract: The present invention relates to a method for visually detecting and tracking an object through a space. The method chooses modules for a restricting a search function within the space to regions with a high probability of significant change, the search function operating on images supplied by a camera. The method also derives statistical models for errors, including quantifying an indexing step performed by an indexing module, and tuning system parameters. Further the method applies a likelihood model for candidate hypothesis evaluation and object parameters estimation for locating the object.

Abstract: The present invention relates to a method for visually detecting and tracking an object through a space. The method chooses modules for a restricting a search function within the space to regions with a high probability of significant change, the search function operating on images supplied by a camera. The method also derives statistical models for errors, including quantifying an indexing step performed by an indexing module, and tuning system parameters. Further the method applies a likelihood model for candidate hypothesis evaluation and object parameters estimation for locating the object.

Abstract: The present invention relates to a method for visually detecting and tracking an object through a space. The method chooses modules for a restricting a search function within the space to regions with a high probability of significant change, the search function operating on images supplied by a camera. The method also derives statistical models for errors, including quantifying an indexing step performed by an indexing module, and tuning system parameters. Further the method applies a likelihood model for candidate hypothesis evaluation and object parameters estimation for locating the object.

Abstract: A technique is disclosed for building a vision system. Reusable components and replacement components of an existing vision system are identified. The replacement components may be modules that are influenced by the relaxation in application constraints. Statistical characterization is performed on the replacement components (or the hybrid design variations obtained by fusing modules with the replacement modules). Wrappers are developed that provide statistical consistency with existing interfaces and are integrated into the new vision system.

Abstract: The present invention relates to a method for visually detecting and tracking an object through a space. The method chooses modules for a restricting a search function within the space to regions with a high probability of significant change, the search function operating on images supplied by a camera. The method also derives statistical models for errors, including quantifying an indexing step performed by an indexing module, and tuning system parameters. Further the method applies a likelihood model for candidate hypothesis evaluation and object parameters estimation for locating the object.

Abstract: The present invention relates to a method for visually detecting and tracking an object through a space. The method chooses modules for a restricting a search function within the space to regions with a high probability of significant change, the search function operating on images supplied by a camera. The method also derives statistical models for errors, including quantifying an indexing step performed by an indexing module, and tuning system parameters. Further the method applies a likelihood model for candidate hypothesis evaluation and object parameters estimation for locating the object.

Abstract: A technique is disclosed for building a vision system. Reusable components and replacement components of an existing vision system are identified. The replacement components may be modules that are influenced by the relaxation in application constraints. Statistical characterization is performed on the replacement components (or the hybrid design variations obtained by fusing modules with the replacement modules). Wrappers are developed that provide statistical consistency with existing interfaces and are integrated into the new vision system.