Abstract: A method for multiple sensor calibration and tracking, the method including identifying a non-permanent object in a first field of detection (FOD) of a sensor, wherein the sensor is one of a plurality of sensors positioned in various locations at a site, each sensor has a corresponding FOD; tracking the identified object by single-sensor tracking in the first FOD; predicting appearance of the object, and based on the predictions initiating single-sensor tracking in at least one other FOD where it is predicted that the object will appear; and outputting data captured from the tracked FODs.

Abstract: A robotic system (“new robot”) operative for performing at least one task in an environment, the system comprising: learn-from-predecessor functionality governed by a data exchange protocol, which controls short-range wireless knowledge transfer from a short-range wireless transmitter in a predecessor robot system (“old robot”) to a short-range wireless receiver in said robotic system, said knowledge comprising at least one environment-specific datum previously stored by the predecessor robot.

Abstract: Disclosed are systems and devices for facilitating audiovisual communication. According to embodiments, there may be provided a communication device including or otherwise functionally associated with a video camera to acquire visual information from a scene and to convert the visual information into a video stream. A video processing circuit may (a) receive the video stream, (b) extract user related features from the video stream; and (c) detect and characterize one or more user actions. A controller to receive the video processing circuit output and responsive to an indication of one or more detected events within the video stream to trigger a communication session between said communication device and an addressee device, wherein different addressee devices may be associated with different detected actions.

Abstract: A system and method for accent invariant speech recognition comprising: maintaining a database scoring a set of language units in a given language, and for each of the language units, scoring audio samples of pronunciation variations of the language unit pronounced by a plurality of speakers; extracting and storing m the database a feature vector for locating each of the audio samples in a feature space; identifying pronunciation variation distances, which are distances between locations of audio samples of the same language unit in the feature space, and inter-unit distances, which are distances between locations of audio samples of different language units in the feature space; calculating a transformation applicable on the feature space to reduce the pronunciation variation distances relative to the inter-unit distances; and based on the calculated transformation, training a processor to classify as a same language unit pronunciation variations of the same language unit.

Abstract: A method of training a heterogeneous sensory system, including: accepting data of an environment from a first sensor, identifying objects in the data from the first sensor by a first processing unit, accepting data of the environment from a second sensor corresponding to the data of the first sensor, identifying objects in the data from the second sensor by a second processing unit, comparing the identified objects from the first processing unit and the corresponding objects from the second processing unit with a system processing unit, determining cases of discrepancies, between the objects identified in the data of the first sensor and not in the data of the second sensor or vice versa, tagging the data of the cases with discrepancies, storing the tagged data in a training buffer; and training the first processing unit and/or the second processing unit with the data stored in the training buffer.

Abstract: This application discloses to methods, circuits, devices, assemblies and systems for generating a searchable real-scene database including records indicating entities and physical events occurring within the real-scene. The said system may include a camera feed interface to receive a camera feed from each of one or more cameras observing the real-scene. It may also include image processing circuitry including a static scene analysis unit to: (a) extract features of entities appearing in a camera feed, (b) recognize entity types of entities appearing in the one or more camera feeds, (c) assign an entity designator to a specific entity appearing in the camera feeds, (d) generate an entity designator record for a uniquely identifiable entity, and generate an attribute record for a uniquely identifiable entity.

Abstract: A computerized method for providing no-configuration object recognition video analytics, the method comprising generating a database stored in computer memory and including labelled images of recognized objects imaged at an initial set of sites including at least one site; using the database as a training set to train a pattern recognition engine; uploading images of additional site/s including at least one additional site which is not a member in the initial set of sites; providing object recognition results for the additional site/s by using the pattern recognition engine on the images as uploaded; verifying the object recognition results; and using a processor for operating the pattern recognition engine on images generated at each the additional site/s including modifying the pattern recognition engine according to and when indicated by the verifying, thereby to provide no-configuration object recognition video analytics at the additional site/s.

Abstract: The present invention includes computer vision based driver assistance devices, systems, methods and associated computer executable code (hereinafter collectively referred to as: “ADAS”). According to some embodiments, an ADAS may include one or more fixed image/video sensors and one or more adjustable or otherwise movable image/video sensors, characterized by different dimensions of fields of view. According to some embodiments of the present invention, an ADAS may include improved image processing. According to some embodiments, an ADAS may also include one or more sensors adapted to monitor/sense an interior of the vehicle and/or the persons within. An ADAS may include one or more sensors adapted to detect parameters relating to the driver of the vehicle and processing circuitry adapted to assess mental conditions/alertness of the driver and directions of driver gaze. These may be used to modify ADAS operation/thresholds.

Abstract: Disclosed is a system for automatically navigating a vehicle, which system comprises: a data storage containing one or more maps of one or more areas; electronic interfaces for: (i) receiving data relating to the one or more areas from external data sources; (ii) receiving parameters relating to motion of the vehicle from physical sensors; and (iii) receiving a location of the vehicle from a positioning device; a navigation processor comprising processing circuitry adapted to determine an initial optimal route for traversing the vehicle from a given point in the one or more areas to another point in the one or more areas by computationally resolving a constrained minimization problem.