Bar-ilan University

Gal Kaminka

Assaf Friedler

Yehuda Elmaliach

Ari Yakir

Dan Erusalimchik

Meir Kalech

Eliahu Khalastchi

Raz Lin

Eran Sadeh-Or

Shahar Moshe Kosti

David Sarne

An automatic method for autonomous interactions between robots, comprising an action of automatically receiving, by a transport robot, a request for transporting a service robot. The method comprises an action of automatically computing a location of the service robot. The method comprises an action of automatically moving the transport robot to the location of the service robot. The method comprises an action of automatically sending a signal from the service robot to the transport robot using a signal emitter incorporated into a mechanical element attached to the service robot. The method comprises an action of automatically coupling, using the signal, the mechanical element to a carrier element attached to the transport robot.

Robotic cooperative system

A method and a for location-based image retrieval, the method comprising using at least one hardware processor for: receiving N-dimensional coordinates of a point of interest, wherein N is an integer equal to or larger than 2; and retrieving one or more digital images in which the point of interest is visible. In addition, a computer program product configured to execute this method.

Location-based image retrieval

A method for detecting an anomaly in operation of a data analysis device, comprising: receiving present real-time readings of multiple sensors associated with the data analysis device, and maintaining a history of past real-time readings; determining which of said multiple sensors are correlated; computing a deviation between at least some of said present and at least some of said past real-time readings of said correlated sensors; and declaring an anomaly when said deviation exceeds a predetermined threshold.

Anomaly detection methods, devices and systems

Methods and apparatus for image matching using local features, in particular a method and apparatus for flexible interest point computation. The method involves producing multiple octaves of a digital image, wherein each octave of said multiple scale octaves comprises multiple layers; initiating a process comprising detection and description of interest points, wherein said process is programmed to progress layer-by-layer over said multiple layers of each of said multiple octaves, and to continue to a next octave of said multiple octaves upon completion of all layers of a current octave of said multiple octaves; upon the detection and the description of each interest point of said interest points during said process, recording an indication associated with said interest point in a memory, such that said memory accumulates indications during said process; and upon interruption to said process, returning a result being based at least on said indications.

Flexible computer vision

Growing community of inventors

Kfar Saba, Israel

Gal Kaminka