Adeia Semiconductor Bonding Technologies Inc.

Fotonation Limited

Fotonation Vision Limited

Tessera Technologies Ireland Limited

Digitaloptics Corporation Mems

Fotonation Ireland Limited

Adeia Imaging LLC

Fotonation Holdings, LLC

Tobii Technlologies Limited

Petronel Bigioi

Peter Corcoran

Eran Steinberg

Yury Prilutsky

Alexandru Drimbarean

Alexei Pososin

Stefan Petrescu

Adrian Zamfir

Florin Nanu

Mihai Ciuc

Mihnea Gangea

Piotr Stec

Adrian Dorin Capata

Michael J DeLuca

Marta Zamfir

Corneliu Zaharia

Vasile Buzuloiu

Danutz Ursu

Constantin Vertan

Stefanita Ciurel

Istvan Andorko

Igor Barcovschi

Emilian David

Christopher Dainty

Eric L Zarakov

Constantin Vertran

Catalina Neghina

Gabriel Costache

Szabolcs Fulop

Leo Blonk

Corneliu Florea

Roman Gutierrez

Xiaolei Liu

Ilariu Raducan

Valentin Mocanu

Jose A Mendez

Pat K Leang

Ferenc Papai

Andrei Vasiliu

Mihnea Gângea

Mihai Ianculescu

Felix Albu

Mihai Constantin Munteanu

Vlad Georgescu

Alexandru Malaescu

Alexander Goncharov

Larry Murray

George Susanu

Brian O'Sullivan

Serghei Carateev

Vlad Poenaru

Sumat Mehra

Barry McCullagh

Takanori Miki

Bogdan Sultana

Radu Nicolau

Vlad Ionut Ursachi

Gyorgy Simon

Cian Ryan

Joseph Lemley

Bogdan Sandoi

Cosmin Toca

Tudor Topoleanu

Erik Zarakov

Constantin Verlan

Piotr Støc

Darragh Ballesty

Alex Drimbarean

Peter Corooran

A system for generating motion blur comprises: a frame camera, an event camera and an accumulator for accumulating event information from a plurality of events occurring within a window around the exposure time of an image frame in a plurality of event frames. A processor determines from the events in at least a first of the plurality of event frames, one or more areas of movement within the field of view of the event camera; determines from the events in at least a second of the plurality of event frames, a direction of movement for the one or more areas of movement; and applies blur in one or more areas of the image frame corresponding to the one or more determined areas of movement in accordance with at least the direction of movement for each of the one or more areas of movement to produce a blurred image.

System for generating motion blur

A method and system for detecting facial expressions in digital images and applications therefore are disclosed. Analysis of a digital image determines whether or not a smile and/or blink is present on a person's face. Face recognition, and/or a pose or illumination condition determination, permits application of a specific, relatively small classifier cascade.

Detecting facial expressions in digital images

A method for identifying a gesture from one of a plurality of dynamic gestures, each dynamic gesture comprising a distinct movement made by a user over a period of time within a field of view of an image acquisition device comprises iteratively: acquiring a current image from said image acquisition device at a given time; and passing at least a portion of the current image through a bidirectionally recurrent multi-layer classifier. A final layer of the multi-layer classifier comprises an output indicating a probability that a gesture from the plurality of dynamic gestures is being made by a user during the time of acquiring the image.

Method for identifying a gesture

A vehicle occupant monitoring system, OMS, comprises an image acquisition device with a rolling shutter image sensor configured to selectively operate in either: a full-resolution image mode where an image frame corresponding to the full image sensor is provided; or a region of interest, ROI, mode, where an image frame corresponding to a limited portion of the image sensor is provided. An object detector is configured to receive a full-resolution image from the image sensor and to identify a ROI corresponding to an object of interest within the image. A controller is configured to obtain an image corresponding to the ROI from the image sensor operating in ROI mode, the image having an exposure time long enough for all rows of the ROI to be illuminated by a common pulse of light from at least one infra-red light source and short enough to limit motion blur within the image.

Vehicle occupant monitoring system including an image acquisition device with a rolling shutter image sensor

A depth sensing camera system that comprises one or more fisheye lenses and infrared and/or near-infrared image sensors. In some examples, the image sensors may generate output signals based at least in part on receiving radiation via the fisheye lenses. A depth measurement may be calculated based at least in part on the output signals. For example, these output signals may be provided as input to a depth model, which may determine the depth measurement. In some examples, such a depth model may be integrated into an application-specific integrated circuit and/or may be operated by an application processor.

Depth sensing camera system

A vehicle occupant monitoring system, OMS, comprises: an image acquisition device comprising an image sensor and a lens assembly having a varying transmissivity across a field of view of the image sensor; at least one infra-red, IR, light source disposed within a cabin of the vehicle and being configured to illuminate at least one occupant of the vehicle with varying illumination across the field of view of the image sensor; and an image processing pipeline configured to obtain and pre-process an image acquired from the image sensor in accordance with a lens shading map and a cabin illumination map in order to compensate for both the varying transmissivity and the varying illumination in order to provide a more uniformly illuminated image to a controller for further analysis.

An image processing system is configured to receive a first high resolution stream of images and a second lower resolution stream of images from image sources with substantially the same field of view. The system comprises a localizer component configured to provide a location for any object of interest independently of class within successive images of the second stream of images; a classifier configured to: receive one or more locations selectively provided by the localizer, identify a corresponding portion of an image acquired from the first stream at substantially the same time at which an image from the second stream in which an object of interest was identified and return a classification for the type of object within the identified portion of the image from the first stream; and a tracker configured to associate the classification with the location through acquisition of successive images in the second stream.

Image processing system

A method of generating a digital video image uses a wide-angle field of view (WFOV) lens positioned closely in front of an image sensor array so that the image field of the lens is so curved at the sensor array that different regions of the image field are substantially in focus on the sensor array for different positions of the lens. The method comprises selecting a desired region of interest in the image field of the lens, and adjusting the lens/array distance to bring the region of interest into focus on the sensor array. The in-focus region of interest is stored and at least partially corrected for field-of-view distortion due to the WFOV lens. The corrected image is displayed, locally and/or remotely. These steps are cyclically repeated to provide the video image.

Method of generating a digital video image using a wide-angle field of view lens

A vehicle occupant monitoring system, OMS, comprises an image acquisition device with a rolling shutter image sensor comprising an array of sub-pixels which are respectively selectively sensitive to: red and infra-red; blue and infra-red; and green and infra-red light. The device is configured to selectively operate in either: a colour mode where a multi-plane image frame corresponding to the full image sensor is provided, each plane derived from red, green or blue sensitive sub-pixels respectively; or a monochrome mode, where sensor information from sub-pixels is aggregated to provide a single image plane.

A method of responding to a criterion-based request for information collected from users meeting the criterion while complying with a user-requested privacy requirement. In one embodiment a request is received for data comprising facial or audio expressions for users who meet the criterion. A program monitors activities indicative of user attention or user reaction based on face tracking, face detection, face feature detection, eye gaze determination, eye tracking, audio expression determination, or determination of an emotional state. When a user requests a high level of privacy, the timestream data collected for the user is aggregated with timestream data collected for other users into a statistical dataset by processing the timestreams to ensure the high level of privacy in the statistical dataset which is provided to a content provider without providing data collected for the user who has requested the high level of privacy.

Anonymizing facial expression data with a smart-cam

A handheld computing device comprises a display comprising an array of pixels illuminated by a plurality of visible light sources, and a plurality of infra-red light sources interleaved between the visible light sources, the IR light sources being actuable to emit diffuse IR light with a first intensity. A camera has an image sensor comprising an array of pixels responsive to infra-red light and a lens assembly with an optical axis extending from the image sensor through the surface of the display. A dedicated illumination source is located outside the display and is actuable to emit infra-red light with a second greater intensity. A processor is configured to switch between an iris region processing mode in which a subject is illuminated at least by the dedicated light source and a face region processing mode in which a subject is illuminated by the plurality of IR light sources.

Handheld computing device

An image acquisition system determines first and second sets of points defining an iris-pupil boundary and an iris-sclera boundary in an acquired image; determines respective ellipses fitting the first and second sets of points; determines a transformation to transform one of the ellipses into a circle on a corresponding plane; using the determined transformation, transforms the selected ellipse into a circle on the plane; using the determined transformation, transforms the other ellipse into a transformed ellipse on the plane; determines a plurality of ellipses on the plane for defining an iris grid, by interpolating a plurality of ellipses between the circle and the transformed ellipse; moves the determined grid ellipses onto the iris in the image using an inverse transformation of the determined transformation; and extracts an iris texture by unwrapping the iris and interpolating image pixel values at each grid point defined along each of the grid ellipses.

Image acquisition system for off-axis eye images

A method for calibrating a vehicle cabin camera having: a pitch, yaw and roll angle; and a field of view capturing vehicle cabin features which are symmetric about a vehicle longitudinal axis comprises: selecting points from within an image of the vehicle cabin and projecting the points onto a 3D unit circle in accordance with a camera projection model. For each of one or more rotations of a set of candidate yaw and roll rotations, the method comprises: rotating the projected points with the rotation; flipping the rotated points about a pitch axis; counter-rotating the projected points with an inverse of the rotation; and mapping the counter-rotated points back into an image plane to provide a set of transformed points. A candidate rotation which provides a best match between the set of transformed points and the locations of the selected points in the image plane is selected.

Method for calibrating a vehicle cabin camera

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Galway, Ireland

Petronel Bigioi