Abstract: There is provided a computer implemented method of detecting an attempt to breach security of an iris recognition system by an artificial iris, comprising: analyzing at least a portion of a limbal ring depicted in an image of an iris of an individual captured by an imaging sensor at a wavelength range within at least one of near infrared (NIR) and short wave infrared (SWIR), and detecting likelihood of an artificial iris worn by the individual according to the analysis of the at least the portion of the limbal ring.

Abstract: System and methods for enhancing the media consumption experience through generative AI-powered interactive companions. The system monitors media content in real-time, detects predefined cues, and generates contextually relevant and emotionally engaging reactions using a generative language model. These reactions are played and/or presented to the user, simulating an interactive conversation. The AI companion may adapt its responses based on user preferences, emotional states, and the context of the media content. By offering personalized interactions, emotional support, and/or contextual relevance, an immersive, engaging, and emotionally satisfying experience for users may be provided. The systems and methods may be used in entertainment, education, therapy, and social domains.

Abstract: Disclosed herein is a method of improving computation of a 3 dimensional (3D) model of an object, comprising adjusting one or more illumination parameter of one or more light sources illuminating a target object having one or more high reflection surfaces, and operating one or more image sensors to capture a plurality of images depicting the target object from a plurality of different viewpoints while the object is illuminated by the one or more light sources. Wherein the plurality of images are used by one or more processors to compute a 3D model of the target object based on a plurality of features extracted from the plurality of images.

Abstract: A method of detecting three dimensional (3D) changes in sites, comprising receiving a plurality of images of a site captured from a plurality of viewpoints by image sensor(s) mounted on dynamic vehicle(s) scanning the site, registering at least some of the images to each other, creating one or more merged representations of at least part of the site based on the at least some registered images, comparing between the merged representation(s) and one or more corresponding previous merged representations created based on a plurality of previous images captured during one or more previous scans of the site, detecting, based on the comparison, one or more 3D changes indicative of a depth change exceeding a certain threshold in one or more 3D features at the site, and generating a change indication indicative of the one or more detected 3D changes.

Abstract: There is provided a computer implemented method of validation of a human user, comprising: feeding a description of a first object into a GenAI model to generate at least one image depicting a plurality of instances of the first object and a plurality of second objects different than the first object, each instance representing a unique variation of the first object, via a user interface presented on a display of a client terminal: presenting the at least one image, presenting instructions for a user to identify common instances of objects having unique variations that are depicted in the at least one image, receiving the user indication, and validating that the user is a human when the common instances of objects identified by the user matches the description of the first object fed into the GenAI model.

Abstract: There is provided a computer implemented method of analyzing a sequence of images for detection of a change in face gesture, comprising: analyzing the sequence of time spaced images depicting a face of a subject to compute a baseline representation denoting a baseline state of the subject, for a respective image of the sequence of time spaced images depicting a face of a subject: extracting a plurality of features from the face of the subject of the respective image, computing a respective representation from the plurality of features, comparing the respective representation to the baseline representation, and detecting a change in face gesture of the subject when the comparison is above a threshold.

Abstract: There is provided a computer implemented method of training a generative model, comprising: clustering training data elements each associated with an indication of a creation entity of creation entities, into clusters, each cluster including training data elements associated with one creation entity of the creation entities, generating training dataset by accessing training data elements from a sub-set of the clusters, each training dataset excluding at least one cluster of the clusters associated with at least creation entity, and training generative models on the training datasets, wherein each trained generative model of trained generative models is trained on training data elements that exclude at least one creation entity, wherein a target data element generated by a certain trained generative model in response to an input prompt excludes influence of the excluded at least one creation entity.

Abstract: System and method for planar navigation for a moving platform utilizing computer vision techniques is disclosed herein. The method includes capturing with a monocular camera an image containing at least two distinct substantially vertical edges positioned around a waypoint, calculating the horizontal coordinate of the waypoint relative to the horizontal coordinates of the edges, and adjusting the moving platform's heading angle to maintain the said position of the navigation goal. The method includes tracking the pixel separation of the edges and terminating navigation of a segment responsive to the pixel separation exceeding a predetermined threshold.

Abstract: A robot and method to lay cable from an unmanned aerial vehicle (“UAV”). The UAV adjusts its elevation and flight path to avoid obstacles on the ground and obstacles at elevation above the UAV and obstacles at elevation below the UAV.

Abstract: There is provided a computer implemented method of detecting an attempt to breach security of an iris recognition system by an artificial iris, comprising: analyzing at least a portion of a limbal ring depicted in an image of an iris of an individual captured by an imaging sensor at a wavelength range within at least one of near infrared (NIR) and short wave infrared (SWIR), and detecting likelihood of an artificial iris worn by the individual according to the analysis of the at least the portion of the limbal ring.

Abstract: A method, apparatus, and computer program product for monocular obstacle detection on a drone flight path. A drone is instructed to move forward at a constant horizontal speed and concurrently perform a planned motion in at least one perpendicular direction. A monocular camera mounted on the drone is operated to capture one or more image pairs comprising at least a first frame captured along the flight path and a second frame captured at a deviation from the flight path effected by the planned motion. The first and second frames are analyzed to determine stereo matching and according thereto estimate a motion vector between the first and second frames for at least one region of interest. In response to determining according to the motion vector that an obstacle is present on the flight path, at least one obstacle detection response pattern is applied.

Abstract: A portal and method for a drone to transit from one side of door to the other. The portal having an opening for each side of the door and having at least two levels, and a temporary landing area. The portal structure with no moving parts that allows the drone to transit the door.

Abstract: Content authenticity mobile devices, systems and methods for authenticating media content in real-time. The device captures media content using sensors and generates a unique visual digital signature by signing the content with a key and recording time and optionally geographic coordinates and/or movement data. This signature is displayed on the device's screen and recorded alongside the content, serving as a tamper-evident seal. The authentication method involves extracting the visual signature and comparing it with the recorded content to verify its authenticity. The system may generate digital certificates reflecting the authenticity status of the content, which can be stored with the content and easily verified by third parties.

Abstract: There is provided a computer implemented method of validation of a human user, comprising: feeding a description of a first object into a GenAI model to generate at least one image depicting a plurality of instances of the first object and a plurality of second objects different than the first object, each instance representing a unique variation of the first object, via a user interface presented on a display of a client terminal: presenting the at least one image, presenting instructions for a user to identify common instances of objects having unique variations that are depicted in the at least one image, receiving the user indication, and validating that the user is a human when the common instances of objects identified by the user matches the description of the first object fed into the GenAI model.

Abstract: System and methods for enhancing the media consumption experience through generative AI-powered interactive companions. The system monitors media content in real-time, detects predefined cues, and generates contextually relevant and emotionally engaging reactions using a generative language model. These reactions are played and/or presented to the user, simulating an interactive conversation. The AI companion may adapt its responses based on user preferences, emotional states, and the context of the media content. By offering personalized interactions, emotional support, and/or contextual relevance, an immersive, engaging, and emotionally satisfying experience for users may be provided. The systems and methods may be used in entertainment, education, therapy, and social domains.

Abstract: A method of self-localizing with respect to surrounding objects, comprising obtaining an approximated geolocation of the vehicle, retrieving mapping data comprising a geolocation of one or more stationary objects located in an area surrounding the approximated geolocation, receiving imagery data of a surrounding environment of the vehicle captured by a plurality of distinct imaging sensors deployed in the vehicle, applying one or more trained machine learning models to identify one or more of the stationary objects in the imagery data, computing a relative positioning of the vehicle with respect to one or more of the stationary objects based on an orientation of each of the plurality of imaging sensors with respect to the stationary object(s), computing an absolute positioning of the vehicle based on the relative positioning and the geolocation of the stationary object(s), and outputting the vehicle's absolute positioning.

Abstract: There is provided a system for guiding a steerable laser to a target object, comprising: at least one processor executing a code for: for each image of a plurality of images captured by an image sensor and obtained in a plurality of iterations: filtering an illumination of a steerable laser overlapping a target object or in near proximity to a target object from the image, to create a filtered image, detecting the target object on the filtered image by a detector model, and generating instructions for at least one of: further directing of the steerable laser for illumination of the target object, and maintaining the illumination of the steerable on the target object.

Abstract: A method of self-localizing with respect to surrounding objects, comprising obtaining an approximated geolocation of the vehicle, retrieving mapping data comprising a geolocation of one or more stationary objects located in an area surrounding the approximated geolocation, receiving imagery data of a surrounding environment of the vehicle captured by a plurality of distinct imaging sensors deployed in the vehicle, applying one or more trained machine learning models to identify one or more of the stationary objects in the imagery data, computing a relative positioning of the vehicle with respect to one or more of the stationary objects based on an orientation of each of the plurality of imaging sensors with respect to the stationary object(s), computing an absolute positioning of the vehicle based on the relative positioning and the geolocation of the stationary object(s), and outputting the vehicle's absolute positioning.

Abstract: A method of detecting three dimensional (3D) changes in sites, comprising receiving a plurality of images of a site captured from a plurality of viewpoints by image sensor(s) mounted on dynamic vehicle(s) scanning the site, registering at least some of the images to each other, creating one or more merged representations of at least part of the site based on the at least some registered images, comparing between the merged representation(s) and one or more corresponding previous merged representations created based on a plurality of previous images captured during one or more previous scans of the site, detecting, based on the comparison, one or more 3D changes indicative of a depth change exceeding a certain threshold in one or more 3D features at the site, and generating a change indication indicative of the one or more detected 3D changes.

Abstract: A method of autonomous vehicle control, comprising: receiving an image of a lenticular human-imperceptible marker embedded in an element of an environment that an autonomous vehicle is moving in, the marker having a pattern usable for determining positional data of the moving vehicle, the image captured using human-invisible light, analyzing the received image of the human-imperceptible marker, and controlling the autonomous vehicle based on the analyzed image of the human-imperceptible marker.