EP1915874A2 - Procede et circuit pour identifier et suivre les yeux de plusieurs observateurs en temps reel - Google Patents

Procede et circuit pour identifier et suivre les yeux de plusieurs observateurs en temps reel

Info

Publication number
EP1915874A2
EP1915874A2 EP06791307A EP06791307A EP1915874A2 EP 1915874 A2 EP1915874 A2 EP 1915874A2 EP 06791307 A EP06791307 A EP 06791307A EP 06791307 A EP06791307 A EP 06791307A EP 1915874 A2 EP1915874 A2 EP 1915874A2
Authority
EP
European Patent Office
Prior art keywords
eye
instance
face
finder
target area
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
EP06791307A
Other languages
German (de)
English (en)
Inventor
Alexander Schwerdtner
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
SeeReal Technologies GmbH
Original Assignee
SeeReal Technologies GmbH
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by SeeReal Technologies GmbH filed Critical SeeReal Technologies GmbH
Publication of EP1915874A2 publication Critical patent/EP1915874A2/fr
Ceased legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
    • G06F3/013—Eye tracking input arrangements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00—General purpose image data processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/18—Eye characteristics, e.g. of the iris
    • G06V40/19—Sensors therefor
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N13/00—Stereoscopic video systems; Multi-view video systems; Details thereof
    • H04N13/30—Image reproducers
    • H04N13/366—Image reproducers using viewer tracking
    • H04N13/368—Image reproducers using viewer tracking for two or more viewers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N13/00—Stereoscopic video systems; Multi-view video systems; Details thereof
    • H04N13/30—Image reproducers
    • H04N13/366—Image reproducers using viewer tracking
    • H04N13/383—Image reproducers using viewer tracking for tracking with gaze detection, i.e. detecting the lines of sight of the viewer's eyes
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03H—HOLOGRAPHIC PROCESSES OR APPARATUS
    • G03H2226/00—Electro-optic or electronic components relating to digital holography
    • G03H2226/05—Means for tracking the observer
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10004—Still image; Photographic image
    • G06T2207/10012—Stereo images

Definitions

  • the invention relates to a method and a circuit arrangement for a contact-free detection and tracking of eye positions or pupils of several observers in real-time mode.
  • the input data includes imagery as a sequence of digital video frames acquired by one or more image sensors.
  • the invention serves to detect the eye positions in a large target area, allows rapid movement of the viewer and determines the coordinate the depth in a large area of for example 0.5 to 3.5 meters.
  • An important field of application of the invention resides in a device for recognizing and tracking the eye positions of observers of autostereoscopic displays. Such displays provide the viewer with a stereoscopic image impression without the need for aids such as polarization glasses.
  • Other applications of the invention include, for example, the video holography and implementations in the field of person, face or gaze direction detection.
  • Autostereoscopic displays in which the display is tracked by a so-called tracking device, provide multiple viewers a large freedom of movement in a large viewer area. The error-free detection and tracking of eyes, eye positions or pupils is also an essential interface between human and machine in these areas of image presentation.
  • a reliable and error-free tracking device is usually not perceived by a viewer. In many applications, however, errors of the tracking system lead to undesirable side effects, which lead to poor reproduction or crosstalk, for example in the area of the 3D representation.
  • a tracking device requires high accuracy, reliability and accuracy. The system must also be sufficiently efficient and accurate to track the significant movements, allowing the viewer maximum freedom of movement in all three spatial directions.
  • Zhiwei Zhu Qiang Ji describes a method for non-contact detection of eyes in real time, which essentially comprises a step for eye detection and a Includes eye tracking step.
  • Eye detection includes a combination of the active illumination method and pattern recognition. After the eyes of a viewer are first recognized, the eyes are followed, this step involving the combination and synthesis of several algorithms and techniques.
  • combination and Synthesis of various means remains the problem that larger and faster head movements in all three coordinate directions can not be tracked in real time and that the delay between delivery of the position data and image acquisition can prevent real-time processing. This concerns in particular the determination of the eye position in depth in unfavorable environmental conditions.
  • the driver's face is always within a predictable range of the dashboard.
  • even small changes occur in vertical and horizontal directions.
  • the real range of motion in the depth is very small, so that usually when using a single camera, the depth position can be extrapolated with sufficient accuracy.
  • the depth should preferably cover a wide range from 0.5 to at least 3.5 meters.
  • To determine the depth on the one hand, several separately arranged cameras are necessary in order to be able to generate images from different directions from the target area.
  • the detection of the eyes at a distance of up to several meters requires a very high resolution of the cameras, resulting in a large amount of data per camera and per video frame.
  • the invention has the object to provide a method which allows to determine the eye positions of several observers, even with larger and abrupt head movements in all three coordinate directions in real time.
  • the method is intended to detect the detection of the eye positions in a large target area, to compensate for rapid movements of the observer and to determine the coordinate of the depth in a large area.
  • the response time between the video recording, ie the reading of a video frame and the result delivery, ie the provision of the eye positions should be sustainably reduced.
  • the method should also allow for high-resolution cameras error-free results in real-time mode can be achieved.
  • the method is used to detect and track reference points of multiple viewer's eyes in real time.
  • the input data includes image data as a sequence of digital video frames acquired by one or more image sensors, such as cameras.
  • the reference points of the eyes are the positions of the pupils and / or the corner of the eye.
  • the method comprises the interaction of a face finder instance for finding faces, subsequently and hierarchically subordinate an eye finder instance for finding areas of the eyes, and an eye tracker Instance used to detect and track eye points.
  • the Eye Tracker instance is hierarchically subordinate to the Eye Finder instance.
  • the invention is based on the idea that the position determination of the eyes is implemented within a hierarchical sequence with the goal that
  • Search range starting from an entire video image successively restrict.
  • the real-time behavior is realized by the hierarchical successive restriction and nesting of the search area from the complete video frame for the face finder instance to the restricted face target area for the eye finder or eye tracker instance.
  • an instance or a group of instances is executed in parallel on a separate computing unit within separate processes.
  • the Face Finder instance searches the head or face position for each viewer in the area of an entire video frame. For each face, the instance determines a significantly smaller amount of data from the data of the entire video frame, representing the corresponding face-target area, and passes that restricted area to the Eye-Finder instance.
  • the eye finder instance is hierarchically subordinate to the face finder instance and only needs to process a very limited amount of data from the data of the passed face target area.
  • the instance determines the eyes or eye positions in this data area and, in turn, defines a much smaller data volume of the face / target area than the eye / target area, whereby this limited search area is then transferred to a subsequent and hierarchically subordinate eye tracker instance.
  • the Eye Tracker Instance determines the sought reference points of the eyes in this highly constrained amount of data of the eye search area at an increased speed.
  • the Eye Tracker instance is highly effective and fast.
  • the instances face-finder and eye-finder / eye tracker should each be executed in parallel independently of each other within separate processes.
  • the parallelization by assigning an instance or a group of instances to its own computing units can be implemented in several variants.
  • a face-Finder instance is performed on a separate computing unit for each camera. Subsequently, each observer, who finds a face finder instance, is assigned an own arithmetic unit for the realization of an eye finder and subsequently an eye tracker instance. If a newly detected face is determined by a face finder instance, an instance of the eye finder and the eye tracker is immediately commissioned or initialized and these instances are executed on their own assigned arithmetic unit. Even for briefly lost and rediscovered faces an immediate tracking is delegated after detection of the face.
  • a significant advantage of the invention is that a face-Finder instance, since now the subordinate instances are executed on their own arithmetic units, is in no way blocked or obstructed.
  • the Face Finder instance continues to search for faces in the data of the current video frame, while preserving the computational resources. Determined intermediate and partial results are transferred to a control entity for further processing / distribution, or they are taken over by partial results of the eye tracker / eye finder instances in order to be able to extrapolate the facial target areas in a positive control loop.
  • the immediate realization of the instances shortens the response time of the process and provides the first basis for real-time behavior.
  • the real-time behavior is provided by the hierarchical successive restriction and nesting of the search area from the complete video frame for the Underpinned Face Finder instance to the restricted face target area for the Eye Finder or Eye Tracker instance.
  • real-time behavior is further underpinned and secured by the implementation of an instance or a group of instances in parallel within separate processes on a separate computing unit.
  • a face finder instance and an eye finder / eye tracker instance can each be executed on a separate arithmetic unit.
  • a face finder / eye finder instance and an eye tracker instance can be executed on a separate arithmetic unit.
  • An implementation of the Eye Finder instance on its own arithmetic unit also seems conceivable. However, this is an instance which requires a comparatively short computing time, so that it is advantageously allocated to a computing unit of the two computing intensive face finders or eye tracker instances.
  • both the flow of the instances and their data exchange is controlled and monitored by a control entity.
  • this instance controls the assignment of the found faces, or face target areas, to the eye finder / eye tracker instances on the individual arithmetic units.
  • the data exchange essentially comprises the
  • Initialization of the instances by assigning the search areas, the exchange of partial and final results of the instances and the transfer of the resulting reference points for the eyes to an external interface.
  • the control instance updates and re-initializes the associated instances of the Eye Finder and the Eye Tracker for an already tracked face.
  • the tax authority selects, verifies and evaluates the confidence of the found face and eye target areas.
  • Corresponding evaluation parameters are determined by the instances in the course of the procedure and serve the control entity also for an optimal execution coordination of the instances and as well as an allocation of the existing calculation units.
  • the method according to the invention allows the eye positions of several observers even with larger and abrupt head movements in all three To determine coordinate directions in real time.
  • the method can also achieve results in the real-time mode for the data volume of high-resolution camera systems.
  • Fig. 1 is a schematic representation of the nested, restricted
  • Fig. 3 is a schematic representation of the circuit arrangement and a flowchart of the parallelization of the hierarchically structured instances of the method according to the invention.
  • Fig. 1 shows the interleaved, restricted search areas of the instances of the method.
  • image material is acquired as a sequence of digital video frames VF from a plurality of image sensors, for example a stereo infrared camera.
  • a section of the entire video frame VF is shown schematically in the figure by the coordinate system.
  • a first face finder instance analyzes the data of the entire video frame VF and recognizes the faces of the viewers throughout the video frame. In the figure, the data of two faces are shown. The first face on the left is obviously close to the camera, while the second right one has a higher distance to the camera.
  • the face finder instance determines from the data of the entire video frame VF a limited data area of the facial Target area GZ corresponds.
  • the indices refer to the first face shown in the figure on the left.
  • the determined face target area GZ now represents the restricted search area for subsequent Eye Finder instance.
  • the Eye Finder instance determines the eye positions and, as a result, restricts the data volume of the target area GZ to a much smaller amount of data Eye Target Range AZ equals, one.
  • the data of the eye target area AZ with the eye positions are the input data for a subsequent eye tracker instance ET, which is now in the eye target area AZ for the current video frame and in the subsequent video frames according to the already determined motion sequence in the guided eye target area AZ finally determined reference points for the eyes as a result.
  • the eye target area AZ is tracked, updated and the areas for the current and the coming frames are extrapolated. If the observer moves into the depth, a scaling of the image content may additionally be necessary.
  • the eye-target area can disintegrate into several non-contiguous subregions.
  • the target areas are irregular, but preferably convex, depending on the observer's head position and viewing direction.
  • the regions are represented by a list of parameterized geometric surfaces, such as ellipses, circles, or rectangles.
  • Fig. 2 builds on the last embodiment and shows a flowchart of the parallelization of the instances.
  • the figure describes the hierarchical structuring of the instances of face finder FF, eye finder and eye tracker ET and the assignment to own calculation units R1 to R2.
  • a first arithmetic unit R1 is provided for the face finder instance FF. This finds the face of a first observer in the data of a video frame and thereby determines the facial target area GZ.
  • the facial Zi ⁇ l Symposium is immediately assigned its own arithmetic unit R1 for performing an eye finder EF and subsequently an eye tracker instance ET.
  • the figure shows the data flow of the data of the restricted target areas, ie facial target area GZ and eye target area AZ to the respective subsequent instance.
  • An eye tracker instance ET supplies the data of the reference points of eyes to a superordinate control instance (not shown) or to an external interface.
  • the information of the reference points determined in the past video frames is used to track the eye target area AZ during a movement of the observer and to extrapolate for the coming frames.
  • the data of the current eye target area as well as the areas of past frames are therefore returned to the Eye Tracker instance as shown.
  • an eye-finder eye-tracker instance is preferably realized analogously for each observer, that is to say a face-target area, as independent processes running in parallel, in which case several processes naturally run on one common arithmetic unit.
  • FIGS. 1 and 2 show a circuit arrangement and a flowchart of the parallelization of the hierarchically structured instances a parallelization of the method based on the image data of several cameras different positions
  • the cameras are each based on a method analogous to the above examples.
  • a camera is thus associated with a parallelization of the instances analogous to FIGS. 1 and 2.
  • the left system determines from the left image data VFL (Video Frame Left) by a face finder instance FF on a first of the arithmetic unit R1 the face target area GZ1-L of the first observer.
  • the associated Eye-Finder EF / Eye Tracker ET instances are executed on the arithmetic unit R2.
  • these arithmetic units are usually implemented as CPUs or DSPs.
  • a second group of instances on the arithmetic unit R3 is assigned to a second observer.
  • the remaining instances and arithmetic units shown in the figure refer to the right and the associated instances or elements of the circuit arrangement, characterized by VFR (Video Frame Right) and the index "R".
  • One and possibly also implemented control unit assumes in the process the task of controlling the individual processes and controls the data exchange.
  • the data exchange takes place in particular within those arithmetic units which are assigned to a viewer. For example, one uses the already available information in the left, in the right, whose content is not significantly different from the left, to determine the position in the right image with a certain tolerance and to extrapolate in knowledge of. From the xy pixel position of the eye in the left, the distance of the observer, which was determined from the previous depth calculation, and the camera parameters is a
  • the circuit arrangement essentially comprises communicating, programmable logic modules, processors, ROMs and RAMs.
  • the arithmetic units are optimized and configured exclusively for the intended task, in particular for the named instances.
  • the circuit arrangement also contains independent arithmetic units for performing auxiliary processes, such as scaling, gamma correction or the like.

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Human Computer Interaction (AREA)
  • General Engineering & Computer Science (AREA)
  • Signal Processing (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Health & Medical Sciences (AREA)
  • Ophthalmology & Optometry (AREA)
  • General Health & Medical Sciences (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)
  • Studio Devices (AREA)
  • Testing, Inspecting, Measuring Of Stereoscopic Televisions And Televisions (AREA)
  • Collating Specific Patterns (AREA)

Abstract

L'invention concerne un procédé et un circuit permettant d'identifier et de suivre sans contact la position d'yeux de plusieurs observateurs en temps réel. Les données d'entrée comprennent une séquence de trames vidéo. Ledit procédé comprend les étapes suivantes: faire coopérer une instance de recherche de visage pour trouver des visages, une instance de recherche d'yeux pour trouver certaines zones des yeux et une instance de poursuite oculaire, qui sert à identifier et à poursuivre des points de référence des yeux. L'invention se fonde sur le fait que la position trouvée des yeux à l'intérieur d'un déroulement hiérarchique des instances est convertie dans le but de limiter successivement la quantité de données à traiter, à partir de la quantité de données de l'ensemble de la trame vidéo (VF), à une zone cible du visage (GZ), puis à une zone des yeux (AZ). Par la suite, une instance ou un groupe d'instances sont conduits en déroulement parallèle, dans chaque cas sur une unité de calcul spécifique.
EP06791307A 2005-08-17 2006-08-16 Procede et circuit pour identifier et suivre les yeux de plusieurs observateurs en temps reel Ceased EP1915874A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102005040598 2005-08-17
PCT/DE2006/001437 WO2007019842A2 (fr) 2005-08-17 2006-08-16 Procede et circuit pour identifier et suivre les yeux de plusieurs observateurs en temps reel

Publications (1)

Publication Number Publication Date
EP1915874A2 true EP1915874A2 (fr) 2008-04-30

Family

ID=37654754

Family Applications (1)

Application Number Title Priority Date Filing Date
EP06791307A Ceased EP1915874A2 (fr) 2005-08-17 2006-08-16 Procede et circuit pour identifier et suivre les yeux de plusieurs observateurs en temps reel

Country Status (10)

Country Link
US (1) US7950802B2 (fr)
EP (1) EP1915874A2 (fr)
JP (1) JP5054008B2 (fr)
KR (1) KR101278430B1 (fr)
CN (1) CN101243693B (fr)
BR (1) BRPI0616547A2 (fr)
CA (1) CA2619155A1 (fr)
DE (1) DE112006002752A5 (fr)
RU (1) RU2408162C2 (fr)
WO (1) WO2007019842A2 (fr)

Families Citing this family (40)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4420056B2 (ja) * 2007-04-20 2010-02-24 ソニー株式会社 画像処理装置と画像処理方法および画像処理プログラム、並びに再生情報生成装置と再生情報生成方法及び再生情報生成プログラム
DE102007025069B4 (de) * 2007-05-21 2018-05-24 Seereal Technologies S.A. Holographisches Rekonstruktionssystem
DE102007056528B3 (de) * 2007-11-16 2009-04-02 Seereal Technologies S.A. Verfahren und Vorrichtung zum Auffinden und Verfolgen von Augenpaaren
USRE45394E1 (en) 2008-10-20 2015-03-03 X6D Limited 3D glasses
USD603445S1 (en) 2009-03-13 2009-11-03 X6D Limited 3D glasses
USD624952S1 (en) 2008-10-20 2010-10-05 X6D Ltd. 3D glasses
USD666663S1 (en) 2008-10-20 2012-09-04 X6D Limited 3D glasses
US8542326B2 (en) 2008-11-17 2013-09-24 X6D Limited 3D shutter glasses for use with LCD displays
CA2684513A1 (fr) 2008-11-17 2010-05-17 X6D Limited Lunettes de vision tridimensionnelle ameliorees
USD646451S1 (en) 2009-03-30 2011-10-04 X6D Limited Cart for 3D glasses
US8314832B2 (en) 2009-04-01 2012-11-20 Microsoft Corporation Systems and methods for generating stereoscopic images
US20120105486A1 (en) 2009-04-09 2012-05-03 Dynavox Systems Llc Calibration free, motion tolerent eye-gaze direction detector with contextually aware computer interaction and communication methods
USD672804S1 (en) 2009-05-13 2012-12-18 X6D Limited 3D glasses
USD650956S1 (en) 2009-05-13 2011-12-20 X6D Limited Cart for 3D glasses
ES2669058T3 (es) * 2009-07-16 2018-05-23 Tobii Ab Sistema y método de detección ocular que usa flujo de datos secuencial
JP2011064894A (ja) * 2009-09-16 2011-03-31 Fujifilm Corp 立体画像表示装置
USD669522S1 (en) 2010-08-27 2012-10-23 X6D Limited 3D glasses
USD692941S1 (en) 2009-11-16 2013-11-05 X6D Limited 3D glasses
USD671590S1 (en) 2010-09-10 2012-11-27 X6D Limited 3D glasses
USD662965S1 (en) 2010-02-04 2012-07-03 X6D Limited 3D glasses
USD664183S1 (en) 2010-08-27 2012-07-24 X6D Limited 3D glasses
US9235754B2 (en) 2011-03-28 2016-01-12 Nec Corporation Person tracking device, person tracking method, and non-transitory computer readable medium storing person tracking program
WO2013046100A1 (fr) * 2011-09-28 2013-04-04 Koninklijke Philips Electronics N.V. Détermination de la distance à un objet à partir d'une image
USD711959S1 (en) 2012-08-10 2014-08-26 X6D Limited Glasses for amblyopia treatment
US9265458B2 (en) 2012-12-04 2016-02-23 Sync-Think, Inc. Application of smooth pursuit cognitive testing paradigms to clinical drug development
KR102175853B1 (ko) * 2013-02-22 2020-11-06 삼성전자주식회사 동작 제어 방법 및 그 전자 장치
RU2530660C1 (ru) * 2013-02-26 2014-10-10 Владимир Николаевич Антипов Способ выявления диапазона условий восприятия глубины образов плоскостных изображений
US9380976B2 (en) 2013-03-11 2016-07-05 Sync-Think, Inc. Optical neuroinformatics
RU2541922C2 (ru) * 2013-05-14 2015-02-20 Федеральное государственное бюджетное учреждение "Национальный исследовательский центр "Курчатовский институт" Способ и устройство определения направленности взгляда
KR102093455B1 (ko) * 2013-10-04 2020-03-25 한국전자통신연구원 하이브리드 카메라에 기초한 동공 추적을 이용한 홀로그램 표시 장치 및 방법
TWI522257B (zh) * 2014-07-09 2016-02-21 原相科技股份有限公司 車用安全系統及其運作方法
CN104661012B (zh) * 2014-11-28 2017-12-01 深圳市魔眼科技有限公司 个人全息三维显示方法及设备
CN104581126A (zh) * 2014-12-16 2015-04-29 青岛歌尔声学科技有限公司 一种头戴显示设备的画面显示处理方法和处理装置
CN107837089B (zh) * 2017-12-05 2018-11-23 清华大学 一种基于脑电波的视频卡顿极限值测量方法
US10951875B2 (en) 2018-07-03 2021-03-16 Raxium, Inc. Display processing circuitry
US10930183B2 (en) 2018-11-22 2021-02-23 Electronics And Telecommunications Research Institute Hologram content generation apparatus, integrated hologram content control system having the same, and method for operating the hologram content generation apparatus
US11619825B2 (en) 2019-04-10 2023-04-04 Electronics And Telecommunications Research Institute Method and apparatus for displaying binocular hologram image
US11474597B2 (en) 2019-11-01 2022-10-18 Google Llc Light field displays incorporating eye trackers and methods for generating views for a light field display using eye tracking information
US11699242B2 (en) 2020-02-25 2023-07-11 Electronics And Telecommunications Research Institute System and method for digital hologram synthesis and process using deep learning
US11532122B2 (en) 2020-03-05 2022-12-20 Electronics And Telecommunications Research Institute Method and apparatus for processing holographic image

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH08147477A (ja) * 1994-09-20 1996-06-07 Fujitsu Ltd 局所領域画像追跡装置
DE69507594T2 (de) * 1995-03-31 1999-09-02 Hitachi Europe Ltd. Bildverarbeitungsverfahren zur Ermittlung von Gesichtsmerkmalen
DE69524204T2 (de) * 1995-03-31 2002-08-22 Hitachi Europe Ltd., Maidenhead Gesichtsbildverarbeitung
US5912980A (en) * 1995-07-13 1999-06-15 Hunke; H. Martin Target acquisition and tracking
US5867587A (en) * 1997-05-19 1999-02-02 Northrop Grumman Corporation Impaired operator detection and warning system employing eyeblink analysis
GB2363273A (en) * 2000-06-09 2001-12-12 Secr Defence Computation time reduction for three dimensional displays
US6873714B2 (en) * 2002-02-19 2005-03-29 Delphi Technologies, Inc. Auto calibration and personalization of eye tracking system using larger field of view imager with higher resolution
CN1225375C (zh) * 2003-07-02 2005-11-02 北京交通大学 基于多特征融合的困倦驾驶检测方法
JP2005099953A (ja) * 2003-09-22 2005-04-14 Fuji Xerox Co Ltd 画像処理装置、それを備えるオブジェクト追跡システム、画像処理方法及び画像処理プログラム

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See references of WO2007019842A2 *

Also Published As

Publication number Publication date
JP5054008B2 (ja) 2012-10-24
KR20080047392A (ko) 2008-05-28
US7950802B2 (en) 2011-05-31
DE112006002752A5 (de) 2008-08-28
JP2009505247A (ja) 2009-02-05
WO2007019842A3 (fr) 2007-11-29
CN101243693A (zh) 2008-08-13
RU2408162C2 (ru) 2010-12-27
WO2007019842A2 (fr) 2007-02-22
US20080231805A1 (en) 2008-09-25
KR101278430B1 (ko) 2013-06-24
BRPI0616547A2 (pt) 2011-06-21
CA2619155A1 (fr) 2007-02-22
RU2008110044A (ru) 2009-09-27
CN101243693B (zh) 2013-07-31

Similar Documents

Publication Publication Date Title
EP1915874A2 (fr) Procede et circuit pour identifier et suivre les yeux de plusieurs observateurs en temps reel
DE102016212405B4 (de) Fahrzeugbildverarbeitungsvorrichtung und Fahrzeugbildverarbeitungssystem
DE69707886T2 (de) Verfahren und gerät zum lokalisieren einer sich bewegenden zone und bestimmung der schnellheit und richtung der bewegung eines gebietes von relativer bewegung in einer szene
DE102012219834B4 (de) Spurverfolgungssystem
DE112018001050T5 (de) System und verfahren zur virtuell erweiterten visuellen gleichzeitigen lokalisierung und kartographierung
DE102018215344A1 (de) System und verfahren für fahrzeugkonvois
DE102015209822A1 (de) Erfassungseinrichtung, Erfassungsprogramm, Erfassungsverfahren, mit Erfassungseinrichtung ausgerüstetes Fahrzeug, Parameterberechnungseinrichtung, Parameter berechnende Parameter, Parameterberechnungsprogramm, und Verfahren zum Berechnen von Parametern
DE102009012441B4 (de) Verfahren zur Reduktion des Speicherbedarfs bei der Bestimmung von Disparitätswerten für mindestens zwei stereoskopisch aufgenommene Bilder
EP2005361A1 (fr) Detecteur d'objets multi-sensoriel reposant sur des hypotheses et dispositif de suivi d'objets
DE102018201154A1 (de) Verfahren zur Kalibrierung von Sensoren und/oder von Sensoranordnungen
DE102012104302A1 (de) Umgebungserkennungsvorrichtung und Umgebungserkennungsverfahren
DE102014201271A1 (de) Verfahren und Steuergerät zum Erkennen einer Veränderung eines relativen Gierwinkels innerhalb eines Stereo-Video-Systems für ein Fahrzeug
DE102013211671A1 (de) System zum Hervorheben von Zielen an Head-Up-Anzeigen mit Nahfokusebene
DE102012223481A1 (de) Vorrichtung und Verfahren zum Verfolgen der Position eines peripheren Fahrzeugs
DE102018100909A1 (de) Verfahren zum Rekonstruieren von Bildern einer Szene, die durch ein multifokales Kamerasystem aufgenommen werden
EP2676449A2 (fr) Procédé et dispositif d'élargissement de la base stéréo d'images et de successions d'images stéréoscopiques
DE102014219423A1 (de) Dynamisches Modell zur Kompensation von Verzeichnungen einer Windschutzscheibe
EP2192550A1 (fr) Procédé de détermination du changement de position d'un système de caméra et dispositif de détection et de traitement d'images
DE102015205868A1 (de) Verfahren und Vorrichtung zum Betreiben einer Anzeigevorrichtung in einem Kraftfahrzeug
DE102021206608A1 (de) Kamerasystem sowie Verfahren für ein Kamerasystem
EP3568737B1 (fr) Procédé de fonctionnement d'un système d'affichage comportant un visiocasque dans un véhicule automobile
DE112019002126T5 (de) Positionsschätzungsvorrichtung, positionsschätzungsverfahren und programm dafür
DE102019201633A1 (de) Kalibrierung eines Sensors für ein Fahrzeug basierend auf objektseitigen und bildseitigen Identifikationsindizes eines Referenzobjektes
DE102015205077B4 (de) Abstandserkennungsvorrichtung für ein Fahrzeug
EP4246268B1 (fr) Procédé de détermination sécurisée d'un trajet de vol d'un véhicule aérien sans pilote et véhicule aérien sans pilote

Legal Events

Date Code Title Description
PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

17P Request for examination filed

Effective date: 20080306

AK Designated contracting states

Kind code of ref document: A2

Designated state(s): AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HU IE IS IT LI LT LU LV MC NL PL PT RO SE SI SK TR

AX Request for extension of the european patent

Extension state: AL BA HR MK RS

RIN1 Information on inventor provided before grant (corrected)

Inventor name: ZSCHAU, ENRICO

Inventor name: SCHWERDTNER, ALEXANDER

RAP1 Party data changed (applicant data changed or rights of an application transferred)

Owner name: SEEREAL TECHNOLOGIES GMBH

17Q First examination report despatched

Effective date: 20110502

DAX Request for extension of the european patent (deleted)
REG Reference to a national code

Ref country code: DE

Ref legal event code: R003

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE APPLICATION HAS BEEN REFUSED

18R Application refused

Effective date: 20140221