Abstract: A system for creating synthetic data for testing an autonomous system, comprising at least one hardware processor adapted to execute a code for: using a machine learning model to compute a plurality of depth maps based on a plurality of real signals captured simultaneously from a common physical scene, each of the plurality of real signals are captured by one of a plurality of sensors, each of the plurality of computed depth maps qualifies one of the plurality of real signals; applying a point of view transformation to the plurality of real signals and the plurality of depth maps, to produce synthetic data simulating a possible signal captured from the common physical scene by a target sensor in an identified position relative to the plurality of sensors; and providing the synthetic data to at least one testing engine to test an autonomous system comprising the target sensor.

Abstract: A method, system, and computer program product for analyzing images of visual objects, such as currency and/or payment cards, captured on a mobile device. The analysis allows determining the authenticity and/or total amount of value of the currency and/or payment cards. The system may be used to verify the authenticity of hard currency, to count the total amount of the currency captured in one or more images, and to convert the currency using real time monetary exchange rates. The mobile device may be used to verify the identity of a credit card user by analyzing one or more images of the card holder's face and/or card holder's signature, card holder's name on the card, card number, and/or card security code.

Abstract: A computer implemented method of creating a simulated realistic virtual model of a geographical area for training an autonomous driving system, comprising obtaining geographic map data of a geographical area, obtaining visual imagery data of the geographical area, classifying static objects identified in the visual imagery data to corresponding labels to designate labeled objects, superimposing the labeled objects over the geographic map data, generating a virtual 3D realistic model emulating the geographical area by synthesizing a corresponding visual texture for each of the labeled objects and injecting synthetic 3D imaging feed of the realistic model to imaging sensor(s) input(s) of the autonomous driving system controlling movement of an emulated vehicle in the realistic model where the synthetic 3D imaging feed is generated to depict the realistic model from a point of view of emulated imaging sensor(s) mounted on the emulated vehicle.

Abstract: A method, system, and computer program product for analyzing images of visual objects, such as currency and/or payment cards, captured on a mobile device. The analysis allows determining the authenticity and/or total amount of value of the currency and/or payment cards. The system may be used to verify the authenticity of hard currency, to count the total amount of the currency captured in one or more images, and to convert the currency using real time monetary exchange rates. The mobile device may be used to verify the identity of a credit card user by analyzing one or more images of the card holder's face and/or card holder's signature, card holder's name on the card, card number, and/or card security code.

Abstract: A computer implemented method of creating a simulated realistic virtual model of a geographical area for training an autonomous driving system, comprising obtaining geographic map data of a geographical area, obtaining visual imagery data of the geographical area, classifying static objects identified in the visual imagery data to corresponding labels to designate labeled objects, superimposing the labeled objects over the geographic map data, generating a virtual 3D realistic model emulating the geographical area by synthesizing a corresponding visual texture for each of the labeled objects and injecting synthetic 3D imaging feed of the realistic model to imaging sensor(s) input(s) of the autonomous driving system controlling movement of an emulated vehicle in the realistic model where the synthetic 3D imaging feed is generated to depict the realistic model from a point of view of emulated imaging sensor(s) mounted on the emulated vehicle.

Abstract: A system for creating synthetic data for testing an autonomous system, comprising at least one hardware processor adapted to execute a code for: producing a plurality of synthetic training signals, each simulating one of a plurality of signals simultaneously captured from a common training scene by a plurality of sensors, and a plurality of training depth maps each qualifying one of the plurality of synthetic training signals according to the common training scene; training a machine learning model based on the plurality of synthetic training signals and the plurality of training depth maps; using the machine learning model to compute a plurality of computed depth maps based on a plurality of real signals, the plurality of real signals are captured simultaneously from a common physical scene, each of the plurality of real signals are captured by one of the plurality of sensors, each of the plurality of computed depth maps.

Abstract: A computer implemented method of creating a simulated realistic virtual model of a geographical area for training an autonomous driving system, comprising obtaining geographic map data of a geographical area, obtaining visual imagery data of the geographical area, classifying static objects identified in the visual imagery data to corresponding labels to designate labeled objects, superimposing the labeled objects over the geographic map data, generating a virtual 3D realistic model emulating the geographical area by synthesizing a corresponding visual texture for each of the labeled objects and injecting synthetic 3D imaging feed of the realistic model to imaging sensor(s) input(s) of the autonomous driving system controlling movement of an emulated vehicle in the realistic model where the synthetic 3D imaging feed is generated to depict the realistic model from a point of view of emulated imaging sensor(s) mounted on the emulated vehicle.

Abstract: A method of handling multimedia data in which packets of a multimedia file from a first computer are received by a second computer. In case, a sub-portion of the multimedia file, representative of the multimedia file, was received by the second computer, before the entire file was received by the second computer, that sub portion is handled by the second computer transmitting to the first computer, although the entire file was not received by the second computer at the time of the transmission of the result. Additionally, an image processing server is described comprising: a network interface adapted to receive packets, a communication manager adapted to manage reception of multimedia files through the input interface and to conclude when a sub-portion of a multimedia file, representative of the multimedia file received, and an image handling unit configured to handle said sub-portions.

Abstract: Embodiments are provided for determining driving behavior. In an example method for determining driver behavior from a driving session, the method includes obtaining sensor data from a sensor during a driving session, obtaining image data from an imaging device during the driving session, and analyzing at least one of the sensor data and the image data from the driving session, to identify an event of interest. The method further includes assigning a classification to the event of interest according to a correlation between the sensor data for the event of interest and at least one image from the image data for the event of interest, the correlation based on time the sensor data and the image data is obtained during the driving session, and, wherein the at least one image for the event of interest provides the context for the event of interest.

Abstract: A method of alerting a vehicle's driver. The method comprises receiving an azimuth value indicating a gazing direction of a head of the driver from a primary device placed on the driver, receiving a vehicle bearing value indicating a vehicle moving direction of the vehicle driven by the driver, calculating an angular difference between the azimuth value and the vehicle bearing value, generating an alert when the angular difference deviates from an angular threshold, and automatically presenting the alert to the driver in response to the angular difference.

Abstract: A method of handling multimedia data in which packets of a multimedia file from a first computer are received by a second computer. In case, a sub-portion of the multimedia file, representative of the multimedia file, was received by the second computer, before the entire file was received by the second computer, that sub portion is handled by the second computer transmitting to the first computer, although the entire file was not received by the second computer at the time of the transmission of the result. Additionally, an image processing server is described comprising: a network interface adapted to receive packets, a communication manager adapted to manage reception of multimedia files through the input interface and to conclude when a sub-portion of a multimedia file, representative of the multimedia file received, and an image handling unit configured to handle said sub-portions.

Abstract: A system on chip (SoC) having an integrated circuit (IC) integrating into a single chip advance driver assistance systems (ADAS) processing unit(s), application processing unit(s), at least one memory storing ADAS code comprising ADAS computer instructions adapted to be executed on the ADAS processing unit(s) for processing vehicle sensor data and VM code for executing VM(s) on the application processing unit(s) and a hypervisor which manages an execution of at least one operation system of the VM(s) and an access to a processor shared memory of the ADAS processing unit(s) for acquiring an outcome of executing the ADAS computer instructions for the completion of an ADAS enhancing function by the execution of the VM(s) on the application processing unit(s).

Abstract: A computer implemented method of creating data for a host vehicle simulation, comprising: in each of a plurality of iterations of a host vehicle simulation using at least one processor for: obtaining from an environment simulation engine a semantic-data dataset representing a plurality of scene objects in a geographical area, each one of the plurality of scene objects comprises at least object location coordinates and a plurality of values of semantically described parameters; creating a 3D visual realistic scene emulating the geographical area according to the dataset; applying at least one noise pattern associated with at least one sensor of a vehicle simulated by the host vehicle simulation engine on the virtual 3D visual realistic scene to create sensory ranging data simulation of the geographical area; converting the sensory ranging data simulation to an enhanced dataset emulating the geographical area, the enhanced dataset comprises a plurality of enhanced scene objects.

Abstract: A system and method for analyzing and wirelessly transmitting information in real-time, comprising capturing snapshots and videos, by utilizing for example a smartphone. The images are analyzed in conjunction with other system data to provide the user: 3 dimensional images, GPS coordinates, safety alerts, etc. In particular, the system is mountable within a vehicle interior to provide: road conditions, dangerous driving situations, the make/model/manufacturer of surrounding cars, GPS coordinates, and the identity of local businesses. The user may also share the information via wireless transmissions with surrounding users possessing the same system, such as for real-time video gaming systems. And the system may also be detached from the vehicle for use in other scenarios, such as searching a merchant database for matching items and wirelessly sending the information to other system users.

Abstract: A computer implemented method, system and computer program product for identifying the Main Colors and the matching colors of a visual object, and then viewing on a mobile device select items comprising the matching colors, such as from a merchant's catalog. A visual object is analyzed for color content, and the results are stored on a system database located on the device or on a remote server. The color analysis of the objects comprise advanced image processing techniques, such as Main Color extraction using color space transformation comprising HSV, RGB and CYMK to map between pixels in the image. The user can subsequently view a display on their mobile identifying the visual object's Main Colors and at least one Harmonic Color; and then select and view all items (i.e. products in a database) comprising one Harmonic Color, and/or all items of a specific type and Harmonic Color.

Abstract: A method of calculating a commonly driven velocity recommendation, comprising: gathering a plurality of data messages from a plurality of client devices located in a plurality of different vehicles, each data message comprises a current location value, a current bearing value, and a current velocity value estimated for a hosting vehicle; clustering the plurality of data messages in a plurality of clusters by matching the respective location values and bearing values; calculating a commonly driven velocity per cluster of the plurality of clusters by combining data from respective cluster members; and retrieving the commonly driven velocity in response to an indication of a current location and a current bearing thereof which matches location and bearing of members of the respective cluster.

Abstract: A method of enhancing positioning of a moving vehicle based on visual identification of visual objects, comprising obtaining from a location sensor a global positioning and a movement vector of a moving vehicle, capturing one or more images using one or more imaging devices mounted on the moving vehicle to depict at least partial view of a surroundings of the moving vehicle, analyzing the image(s) to identify one or more visual objects having a known geographical position obtained according to the global positioning from a visual data record associated with a navigation map, analyzing the image(s) to calculate a relative positioning of the moving vehicle with respect to the identified visual object(s), calculating an enhanced positioning of the moving vehicle based on the relative positioning and applying the enhanced positioning to a navigation system of the moving vehicle.

Abstract: A method including: clustering a plurality of records, each record comprises at least one object image and at least one textual field associated with the object, to yield a plurality of clusters such that the object images in each cluster exhibit between them a visual similarity above a specified value; associating each cluster with a label by applying a dictionary function to the textual fields of each cluster, wherein the label reflects a common semantic factor of the textual fields of each cluster, wherein the common semantic factor has a value above a specified threshold. Accordingly, the visual similarity provides a measure of resemblances between two visual objects that can be based on at least one of: the fit between their color distribution such as correlation between their HSV color histograms, the fit between their texture, the fit between their shapes, the correlation between this edge histograms and face similarity.

Abstract: A method of analyzing images over time is provided herein. The method includes: capturing a plurality of images each associated with specified objects in specified locations such that a specified area is covered; specifying regions of interest (ROI) in each of the captured images; repeating the capturing with at least one of: a different location, a different orientation, and a different timing such that the captured images are associated with the specified covered area; and comparing the captured imaged produced in the capturing with the captured imaged produced in the repeating of the capturing to yield comparison between the captured objects by comparing specified ROI.

Abstract: Embodiments are disclosed for adjusting a presentation on a head-mounted display (HMD). In one or more example embodiments, a method of dynamically orienting a presentation of a HMD includes gathering HMD sensor data via at least one HMD sensor that is installed on an HMD worn by a driver of the vehicle and gathering vehicle sensor data via at least one vehicle mounted sensor mounted to the vehicle. The example method further includes performing an analysis of the HMD sensor data and of the vehicle sensor data to identify a difference between the HMD sensor data and the vehicle sensor data, and calculating, based on the difference, an orientation of the HMD device in relation to the vehicle. The method further includes adjusting a presentation of data on a display of the HMD device based on the orientation.