N-Trig Ltd.

Pointgrab Ltd.

Microsoft Technology Licensing, LLC

Optinetix (Israel) Ltd.

Pointguard Ltd.

Haim Perski

Meir Morag

Ori Rimon

Rafi Zachut

Amir Kaplan

Jonathan Moore

Eran Eilat

David Bitton

Itamar Roth

Amihai Ben-David

Udi Benbaron

Avish Jacob Weiner

Gabriel Ilan

Ovadya Menadeva

Gilboa Levy

Oran Tamir

Dan Bechar

Roman Shmulevich

Niv Narkiss

A method for multi-touch detection in a touch input device comprising a grid based sensor, the method comprises sampling outputs from a grid based sensor over a first stage of detection, selecting sensor lines based on the sampled outputs, scanning the selected sensor lines along one axis of the grid based sensor over a second stage of detection, and determining positions of user interaction based on outputs sampled in response to scanning the selected sensor lines during the second stage of detection.

Multi-touch detection

Determining occupants' interactions in a space by applying a computer vision algorithm to track an occupant in a set of images of a space to obtain locations in the space of the occupant over time, where a history log of the occupant includes the locations of the occupant in the space over time is created and history logs of a plurality of occupants are compared to extract interaction points between the plurality of occupants.

Method and system for detecting occupant interactions

Method and system for assigning space related resources

Determining occupancy in a space by detecting a suspected object in a first image of a space, creating a bounding shape around the suspected object in the image, the bounding shape being aligned towards the center of the image, tracking a selected feature from within the bonding shape, determining occupancy in the space based on the tracking, and controlling a device based on the occupancy determination.

System and method for computer vision based tracking of an object

A system for determining information regarding at least one object, comprising: a sensor sensitive to capacitive coupling; at least one object adapted to create a capacitive coupling with the sensor when at least one signal is input to the sensor; a detector adapted to measure at least one output signal of said sensor associated with the at least one object, wherein the output signal associated with the at least one object is an object information code.

Apparatus for object information detection and methods of using same

A system and method for computer vision based tracking of a human form may include detecting a shape of an object in an image of a space and determining the probability of object having a human form shape based on movement of the object. If the probability of the object of being of a human form is above a predetermined threshold the object is tracked and if the probability is below the threshold then the tracking is terminated. Occupancy in the space may be determined based on the tracking of the object.

A method for noise reduction in a digitizer includes determining a location of a stylus with a known frequency of emission over a first sampling period, sampling output from a plurality of detecting elements over a second sampling period, identifying detecting elements with sampled output in the second sampling period above a defined threshold in a selected frequency, the selected frequency being close to but different than the known frequency of the stylus, selecting as a candidate carrier of mere noise a detecting element from the detecting elements identified that is spaced away from the determined location of the stylus, and reducing values of output sampled over the second sampling period from at least one other detecting element, in accordance with the output sampled over the second sampling period from the detecting element selected as the candidate carrier of mere noise.

Noise reduction in digitizer system

A system and method for computer vision based tracking of a human form may include receiving a sequence of images, the images including at least one object having a shape of a human form. A first selected feature is tracked from within the human form shaped object. Shape recognition algorithms are applied at a suspected location of the human form shaped object in an image from the sequence of images to detect a shape of a human form in the image and a second feature from within the detected shape of the human form is then selected and tracked, thereby providing verification and updating of the location of the human form shaped object.

A method for testing a digitizer to determine an operative property of the digitizer, wherein the digitizer includes a sensor grid, comprises providing an input signal on a first portion of the sensor grid, detecting at least one output signal in a second portion of the sensor grid responsive to the input signal in the first portion, and determining at least one operative property of the sensor based on the at least one output signal, wherein at least the transmitting, detecting and determining is performed autonomously by the digitizer.

System and method for diagnostics of a grid based digitizer

A detector for providing position detection of objects over a sensor with a first and second set of conductor lines forming a grid with a plurality of junctions there between at which the conductor lines do not contact, includes a signal generator providing a signal to at least one conductor line of the first set of conductor lines, and circuitry detecting output arising from one or both of an electromagnetic stylus and one or more fingers when present. The output arising from each of the one or more fingers is detected from at least one conductor line of the second set of conductor lines in response to the signal provided to the at least one conductor line of the first set of conductor lines. The circuitry detects positions of one or both the electromagnetic stylus and each of the one or more fingers when present responsive to the output detected.

Touch detection for a digitizer

A system and method for computer vision based tracking of a hand may include receiving a sequence of images, the images including at least one object having a shape of a hand. A first selected feature is tracked from within the hand shaped object. Shape recognition algorithms are applied at a suspected location of the hand shaped object in an image from the sequence of images to detect a shape of a hand in the image and a second feature from within the detected shape of the hand is then selected and tracked, thereby providing verification and updating of the location of the hand shaped object.

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Hod-Hasharon, Israel

Haim Perski