EP4285341A1 - Innenraumüberwachungssystem und verfahren zu dessen betrieb sowie fahrzeug mit einem solchen innenraumüberwachungssystem - Google Patents
Innenraumüberwachungssystem und verfahren zu dessen betrieb sowie fahrzeug mit einem solchen innenraumüberwachungssystemInfo
- Publication number
- EP4285341A1 EP4285341A1 EP23718621.8A EP23718621A EP4285341A1 EP 4285341 A1 EP4285341 A1 EP 4285341A1 EP 23718621 A EP23718621 A EP 23718621A EP 4285341 A1 EP4285341 A1 EP 4285341A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- application
- camera
- app2
- app1
- app3
- 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.)
- Withdrawn
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/64—Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/117—Identification of persons
- A61B5/1171—Identification of persons based on the shapes or appearances of their bodies or parts thereof
- A61B5/1176—Recognition of faces
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/96—Management of image or video recognition tasks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
- A61B5/6893—Cars
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30168—Image quality inspection
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30196—Human being; Person
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30232—Surveillance
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30248—Vehicle exterior or interior
- G06T2207/30268—Vehicle interior
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
- G06V20/593—Recognising seat occupancy
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/59—Context or environment of the image inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
- G06V20/597—Recognising the driver's state or behaviour, e.g. attention or drowsiness
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/20—Movements or behaviour, e.g. gesture recognition
Definitions
- the invention relates to a method for operating a camera-based interior monitoring system according to the type defined in more detail in the preamble of claim 1, an interior monitoring system according to the type defined in more detail in the preamble of claim 10 and a vehicle with such an interior monitoring system.
- Vehicles are increasingly being equipped with an interior monitoring system to provide various comfort and/or safety functionalities.
- an interior monitoring system With the help of a seat occupancy sensor and a seat belt sensor, it can be determined, for example, whether a vehicle occupant is not wearing a seat belt while driving the vehicle. In such a case, a warning may be issued.
- an appropriate interior monitoring system is also able to observe vehicle occupants. This makes it possible, for example, to analyze whether the person driving the vehicle is paying enough attention to what is happening on the road, is tired, or to identify people based on biometric characteristics.
- Such tasks or functionalities based on monitoring the vehicle interior using cameras are referred to below as applications.
- different requirements are placed on the optical detection of the vehicle interior. For example, if there is only one person driving the vehicle in the vehicle, the visual monitoring of the vehicle's rear area is irrelevant. If the person driving the vehicle wears glasses that are impermeable to infrared light, it is not possible to detect the blink of an eye or the direction in which the person is looking in the infrared light spectrum, which makes taking camera images in the infrared light spectrum unnecessary. Capturing colored camera images in such a case could be beneficial for other applications. There is only a comparatively low level of detection of people on vehicle seats Camera trigger required. However, if people are to be identified, a higher camera resolution is required in order to be able to recognize biometric characteristics.
- a method and a device for monitoring at least one vehicle occupant and a method for operating at least one assistance device are known.
- the process involves camera-based monitoring of the vehicle occupant in order to record their vital signs. If brightness fluctuations occur in the area surrounding the vehicle, for example because the vehicle is entering a tunnel, the vehicle can detect this and automatically switch the image capture mode of the camera used to monitor the vehicle occupant from capturing color images to capturing images in the infrared light spectrum and vice versa .
- the present invention is based on the object of specifying an improved method for operating a camera-based interior surveillance system, with the help of which it is possible for the interior surveillance system to best fulfill the tasks associated with the provision of at least two different applications.
- this object is achieved by a method for operating a camera-based interior monitoring system with the features of claim 1 as well as a corresponding interior monitoring system with the features of claim 10 and a vehicle with such an interior monitoring system with the features of claim 11.
- At least one camera is used as a sensor to capture camera images.
- a computing unit evaluates corresponding sensor signals and determines configuration values and configures parameters for setting the interior monitoring system depending on the evaluated sensor signals.
- the configuration values of the parameters are determined, for example, by calculation, iterative methods or rules in such a way that a quality of the camera image required for an application can be achieved.
- the generic method is further developed according to the invention in that the computing unit provides at least two applications, which preferably receive the same sensor signals at the same time evaluate the camera and which each require a different configuration value for at least one first parameter in a specific operating situation at the same time, the computing unit determining a current application ranking for a current operating situation and the configuration value required by the application with the higher rank for the first Parameters are set as the target configuration.
- the simultaneous evaluation of the same sensor signals means that the applications work in parallel based on the sensor signals determined and received by the camera.
- the applications provided by the computing unit are sorted according to their “importance” and the interior monitoring system, in particular configuration values of the camera, is ultimately set so that the application with the highest importance works optimally.
- a configuration value corresponding to the target configuration is a minimum configuration value for a parameter that is required for optimal function without restricting an application in an operating situation.
- the corresponding configuration of the parameters means that the camera images generated by the camera and correspondingly the information derived by the computing unit through analysis of the camera images or sensor signals allow the requirements set by the application with the highest importance to be met in the best possible way in the respective operating situation.
- operating situation includes environmental conditions such as brightness, vehicle occupancy, driving status, shadows from objects or sunlight.
- the computing unit An evaluation of the current operating situation is carried out by the computing unit depending on the evaluated sensor signals.
- the sensor signals include the camera images generated by the camera as well as sensor data from other sensors.
- the method according to the invention can be used in a vehicle, whereby, for example, a seat belt sensor, seat occupancy sensor, brightness sensor or even vehicle-intrinsic information such as a speed of movement or acceleration of the vehicle can be used as a sensor or sensor data.
- a vehicle occupant is seated on a specific vehicle seat, the vehicle is moving at a specific speed, certain lighting conditions prevail, or the like, which requires a corresponding reassessment of the respective operating situation and the corresponding reconfiguration of the parameters for setting the interior monitoring system requires.
- a value is assigned to the configuration values of the application and at least one further parameter is configured in accordance with the target configuration required by an application lower in the application ranking if the value of the configuration value of the target configuration of the further parameter of the downstream application is greater than that Importance of the configuration value of the target configuration of the parameter of the higher-level application.
- parameters that are suitable for a more important application can be set are less important, configure them according to the target configuration of the less important application, provided that they are above the minimum configuration value of the more important application.
- the parameters of the higher-level application are overwritten with configuration values of these parameters of the lower-level application setting the camera, provided these are better, ie have a higher value, otherwise the configuration values of the higher-level application are used.
- the value of the configuration values results from technical features, for example a high resolution is more valuable than a low resolution, and a low signal-to-smoke ratio is more valuable than a high signal-to-noise ratio.
- one configuration value is of higher quality than another, for example it can be defined that IR images are of higher quality than RGB images.
- IR images are of higher quality than RGB images.
- the parameters for setting the indoor monitoring system are configured according to the target configuration required by the highest-ranking application, unless the conti guration value of the target configuration of the lower-ranking application is greater.
- no different value can be assigned, for example if the higher-level application requires a short exposure time and the lower-level application requires a long exposure time, then by specifying the same value, the exposure time parameter is always set to the value required by the higher-level application.
- the application with the highest rank is hereinafter referred to as the first application.
- the applications lower in the application ranking are referred to as second and third applications, respectively.
- a first parameter that is fully important for providing the functionality of the first application is then configured to the configuration values for this parameter in accordance with the target configuration of the first application.
- a second configuration value of a parameter which is correspondingly lower in terms of the target configuration for the optimal functioning of the first application compared to the second application, can then be configured in accordance with the target configuration of the second application.
- the configuration value that is lower in the application with respect to the target configuration can then be set to the configuration value corresponding to the target configuration of the third application.
- the method determines a configuration of the camera parameters for each application according to the ranking, so that the functionality is optimized for each application.
- the computing unit dynamically determines the application requirements and/or an application quality required for each application depending on the changing current or future operating situation and determines the application ranking and/or the value of the configuration parameters depending on the application. Requirements and/or the application quality of a respective application.
- the application ranking must be redetermined for each operating situation in order to evaluate the importance of the applications depending on the operating situation. Depending on the operating situation, only the application quality or the application requirements or both at the same time can change for an application.
- the application quality reflects the quality of camera images or the information obtained from them that is required for operation in a current operating situation.
- the quality of the camera images is a measure of whether an application can be operated in a current operating situation.
- optimal configuration values are determined for respective applications by evaluating captured camera images, for example by measuring the current application quality, and determining the configuration values of the camera according to rules, tables, iteration or calculation methods ensure that the specified application quality is achieved for the respective applications, ie the measured one corresponds to the specified application quality. In other words, an optimal, ie target, configuration is determined for each of the applications. Depending on the ranking of the Applications and the value of the configuration values are used to determine the camera setting, which is then used as a basis for all applications at the same time.
- the application requirements are understood to mean the requirements placed on the respective application in a respective operating situation. Specifically, this means which parameters of the camera with which value or which setting under which boundary and environmental conditions or in which operating situation must be configured for the applications, preferably according to their rank.
- the reading of predefined application rules for the “driver monitoring” application or operating situation includes the application requirement that the eyes and mouth of the person driving the vehicle must be visible in camera images and that the signal-to-noise ratio must not fall below a certain signal-to-noise ratio.
- the speed of movement and acceleration of the vehicle can be analyzed using sensor signals in order to detect when the vehicle is braking in front of a traffic light, for example, and when it is standing in front of the traffic light as an application requirement. If the vehicle is at a traffic light, monitoring the fatigue or alertness of the person driving the vehicle is less important in the application ranking.
- the camera as a sensor can be used to detect current situations to draw conclusions about future situations and to derive corresponding application requirements, for example the status of an unoccupied seat will be maintained for a foreseeable period of time, accordingly the rank for monitoring can be set for the future be prioritized accordingly.
- driving through a tunnel is read from an assistance system for a period of time ahead; for this period, for example, the rank for color images can be prioritized accordingly lower.
- the interior monitoring system can be adapted to the preferences of individual vehicle users and the application requirements can be determined.
- facial recognition can be deactivated to protect the privacy of the vehicle user. In this case, facial recognition receives a particularly low rank.
- the “Driver Monitoring” application receives a particularly low rank.
- the scenery captured by the camera is particularly dark, for example, applications that require the capture of camera images in the infrared light spectrum will receive a high rank and applications that require the capture of colored camera images will receive a lower rank, and vice versa if the scenery is particularly bright.
- the location of a vehicle occupant in a vehicle can be determined. If the rear of the vehicle is empty, an application for tracking the head position of vehicle occupants in the rear of the vehicle receives a low ranking.
- sensor data from other sensors can also be taken into account to determine the application ranking.
- Vehicle speed can be used, whereby at a speed of movement below 10 km/h there is no need to monitor the attention and/or tiredness of the person driving the vehicle. Accordingly, these applications receive a particularly low ranking in this operating situation.
- An application-specific priority can also be defined for each application. For example, monitoring vital signs and/or fatigue detection can be given a particularly high priority value and an application for taking selfies can be given a lower priority.
- Estimating the future operating situation preferably includes predicting a period of time in which a person will not blink or until an observed person blinks again. If the person being observed, for example the person driving the vehicle, has blinked, then it is very likely that he or she will not blink again for the next 300 ms, for example. For example, if the camera records camera images at a frequency of 60 images per second, this means that applying driver monitoring for the next 18 camera images is less important because no blink of an eye needs to be detected. Accordingly, the interior monitoring system is set so that for the next 18 camera images there are better operating conditions for carrying out the vital sign monitoring application.
- the application ranking for driver monitoring is advantageously reduced in the period of the future operating situation, so that other applications are given a higher rank compared to driver monitoring and the setting of their parameters ideally enables an optimized function without restrictions, especially if the parameter only has reluctant settings allows, for example long or short exposure time.
- a further advantageous embodiment of the method also provides that, to determine the application quality, at least one of the following is also used as a KPI (Key Performance Index) image quality metrics to be understood are specified and evaluated for checking at least one camera image:
- KPI Key Performance Index
- an artificial neural network can be used to determine the confidence value.
- the listed image quality metrics of the camera images will differ. For example, the operating situation can change in such a way that the lighting of the scenery captured by the camera is changed. If the parameters with which the camera creates camera images remain constant, for example an exposure time or aperture, this will influence the corresponding quality of the captured camera images. For example, an image can then be overexposed or underexposed. If the application quality cannot be influenced by appropriate measures, the rank of the corresponding application can be reduced.
- At least one of the following variables is set by means of, i.e. for setting the target configuration:
- various settings can be made in order to adapt the operation of the interior monitoring system to a respective operating situation.
- the corresponding parameters are configured according to the target configuration required by this application.
- the camera parameters I can create a corresponding application quality. For example, if the scenery captured by the camera is dark, it can be illuminated using the lighting devices and/or the exposure time, ISO sensitivity or aperture of the camera can be adjusted in order to capture a more recognizable camera image. If several people are to be monitored and/or, for example, the view of a camera is obscured, a second or even more cameras can be used to capture the scene.
- the light emission characteristics of the lighting devices can be used to set, for example, whether a lighting device should be operated in a pulsed or continuous manner and at what wavelength or in which wavelength band the respective lighting device should emit light.
- a lighting device can emit cold white, warm white, colored and/or infrared light.
- Different applications may also require focusing at different focal planes. Depending on which application has a high priority in a given operating situation, the focus is on the corresponding focal level.
- a further advantageous embodiment of the method further provides that at least one variable that can be set using the target configuration is also used as an application requirement.
- Applications that require a comparatively high image resolution for example, receive a higher rank in the application ranking. This can be transferred analogously to the other variables listed that can be set using the target configuration. Another example can be found in connection with the cameras used to capture the scenery.
- a first and a second camera capture the scenery, for example a vehicle interior, and the first camera is integrated into a dashboard of the vehicle and aimed at the person driving the vehicle, it can also capture parts of the rear.
- the second camera is, for example, integrated into a B-pillar of the vehicle and aimed at the rear.
- the first camera is then configured according to the target configuration requested by an attention analysis, which requires, for example, the capture of camera images with a particularly high frequency and in the infrared light spectrum, since the “person detection” application is already possible by capturing the rear of the vehicle via the second camera is covered.
- the application quality is preferably predicted, given constant application requirements of at least one application for a future operating situation, from at least one image quality metric or image quality properties determined in the current and/or in a past operating situation, a value derived therefrom. Determining the application quality for a future operating situation makes it possible to make a statement about how extensive the Functionality of a specific application can be provided without possibly changing the configuration of the camera or advantageously being able to maintain a parameter configuration for the unrestricted function. Future operating situations can, for example, be determined using a navigation system through a preview of a route being traveled, for example changed lighting conditions when entering and exiting a tunnel, standing still at a traffic light, alignment with the sun, etc.
- Target configuration values for parameters of various applications can be determined depending on a required application quality can be predicted, in which case, depending on the rank of the applications and/or the value of the configuration values of the parameters, the camera settings are preliminarily configured so that they are available to the applications without delay when the new operating conditions occur and the applications are operational without configuration processes are.
- At least one application is formed by:
- the photo and/or video recording functionality can, for example, be an application for making a video call.
- the applications listed each place individual requirements on the interior monitoring system.
- the respective target configurations for the individual parameters are correspondingly different. These can sometimes be contradictory. For example, determining the viewing direction requires the capture of camera images in the infrared light spectrum and the photo and/or video recording functionality requires the capture of camera images in color.
- Seat occupancy detection and gesture recognition only require camera images with a comparatively low resolution to function correctly. In order to carry out facial recognition, camera images with a high resolution are required.
- the interior monitoring system can have several cameras and one or more lighting devices for illuminating a scene captured by the camera or cameras.
- the cameras can have different structures. For example, some cameras may have a fixed aperture and a fixed focus and other cameras may be provided with a zoom lens, that is, a variable focus and an adjustable aperture. Some cameras can also capture light in the infrared light spectrum and other cameras in the visible spectrum. Some cameras can also detect light in both the infrared light spectrum and the visible range. Analogously, individual lighting devices can also emit light of only a certain wavelength or a wavelength band.
- the lighting devices can be operated continuously or pulsed. To control the lighting devices in pulsed operating mode, they can be controlled with any modulation.
- the computing unit can be formed by a single computing device or can be divided into several computing devices. For example, a first computing device for controlling the camera, a second computing device for evaluating camera images or sensor signals and a third computing device for determining the application requirements, application quality, determining the value of configuration values and/or determining the application ranking be provided.
- At least one camera is integrated into a combination instrument, a head unit, an interior mirror and/or into a roof control unit, in particular with respect to the vehicle transverse axis between the driver and passenger side and preferably with respect to the vehicle vertical axis at least at the height of the steering wheel.
- a camera installed centrally in the vehicle, i.e. a camera that is located between the driver and If it is arranged on the passenger side and at least at the level of the steering wheel, a particularly large field of vision of the vehicle interior can be captured. Due to the arrangement in the front area of the vehicle and orientation towards the rear, it is possible to detect vehicle occupants from the front. This enables the provision of a variety of different applications. This also makes it possible to dispense with additional cameras, which requires the use of the method according to the invention to find a configuration of the parameters used to set the interior monitoring system that is suitable for a respective operating situation and a respective application.
- FIG. 1 shows a schematic top view of a vehicle according to the invention
- FIG. 2 shows a flowchart of a method according to the invention.
- Figure 1 shows a vehicle 3 according to the invention.
- This includes an interior monitoring system 1 according to the invention with at least one camera 1.1, a computing unit 1.2 and several lighting devices 1.3.
- the camera 1.1 is arranged between the driver and passenger sides in relation to the vehicle transverse axis Ax and is positioned at least at the height of the steering wheel in relation to the vehicle vertical axis Az. This enables particularly wide coverage of the vehicle interior, so that not only people sitting in the driver's seat 5.1 or the passenger seat 5.2 can be detected, but also people who are in the rear seat 5.3 located in the rear of the vehicle 3.
- the camera 1.1 is integrated into a head unit 4 of the vehicle 3.
- the vehicle 3 can also have additional cameras, not shown in detail. These can be, for example, an instrument cluster, a roof lining, an A, B or C pillar, a vehicle seat, a dashboard, a roof control unit Interior mirror or the like can be integrated.
- the same also applies to the lighting devices 1.3.
- a lighting device 1.3 can be arranged laterally at a comparatively small distance from a camera 1.1. The provision of several lighting devices 1.3 enables particularly extensive illumination of the vehicle interior, so that the risk of overlooking relevant objects in areas of the vehicle interior that are too dark is reduced.
- FIG. 2 shows a flow chart of a method according to the invention.
- a method step 201 camera images are generated with the camera 1.1. These are read and processed by the computing unit 1.2 to provide multiple applications APP1, APP2 and APP3 at the same time.
- application requirements are determined in a method step 202.
- a predefined target configuration for the interior monitoring system 1 is read from a memory of the computing unit 1.2, a future operating situation is estimated, user settings are read out, camera images are analyzed, for example to detect a blockage of the camera view, to evaluate an illumination situation of the vehicle interior, objects and/or or to detect people or the like.
- a predefined application-specific priority value can also be read for each application APP1, APP2, APP3.
- the computing unit 1.2 determines an application quality to be achieved for each application APP1, APP2, APP3.
- the application quality reflects, for example, an image quality metric of a camera image, for example a pixel saturation, a histogram, a signal-to-noise ratio, an index of structural similarity, an index of complex wavelet structural similarity, and / or a confidence value determined using artificial intelligence.
- Individual applications APP1, APP2, APP3 may require an individual minimum value for certain image quality metrics so that the respective application APP1, APP2, APP3 can fully provide their respective functionality.
- a rank is determined for each application APP1, APP2, APP3, taking into account the application requirements and/or the application quality for an operating situation.
- the ranks of applications APP1, APP2, APP3 are ordered in a method step 205 and an application ranking 2 is formed from this.
- a first application APP1 has a highest rank, followed by a second application APP2 and a third application APP3.
- the computing unit 1.2 can also assign a value to the configuration values of the parameters for APP1, APP2, APP3. If one or more parameters for setting the interior monitoring system 1 are configured according to the target configuration requested by the first application APP1, one or more further parameters can also be configured according to one requested by the downstream applications APP2, APP3, i.e. required for optimal operation of the application Target configuration can be configured if the significance of the configuration value of the additional parameter of the subordinate application APP2, APP3 corresponding to the target configuration is greater than the significance of the parameter corresponding to the target configuration of the higher-level application APP1.
- the configuration value of the further parameter of the downstream application APP2 corresponding to the target configuration is of higher quality compared to the higher-ranking application APP1, so that the function of the application APP1 is fully served and the function is ensured.
- the first application APP1 is superior to the second application APP2 and the second application APP2 is superior to the third application APP3.
- an operating mode manager 6 which can be, for example, a program executed on the computing unit 1.2, checks whether there is a change in the application due to changing operating situations and associated changes in application requirements and/or application quality. Ranking 2 or a new assignment of values for the configuration values of the parameters of the applications APP1, APP2, APP3 came. If this is not the case, no changes are made to the setting of the interior monitoring system 1 and camera images continue to be recorded. However, if the application ranking 2 has changed due to a changed operating situation and/or the significance of the configuration values of the parameters of the respective applications APP1, APP2, APP3 have been changed, then in method step 207 the target configurations for the individual parameters for setting the interior monitoring system 1 determined. These are then set in method step 208 so that the interior monitoring system 1 captures and evaluates camera images according to the new setting.
- Method step 207 may also include estimating future operating situations. Expected application qualities can be predicted for future operating situations for the individual applications APP1, APP2, APP3. This makes it possible to check whether a predetermined target configuration parameter set is suitable for providing the functionalities of the individual applications APP1, APP2, APP3 to a greater extent or with greater reliability. This makes it possible to find a target configuration parameter set that is particularly optimized for the respective operating situation, so that as many applications APP1, APP2, APP3 provided by the computing unit 1.2 as possible work best in the respective operating situation.
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Multimedia (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Surgery (AREA)
- Public Health (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Biophysics (AREA)
- Animal Behavior & Ethology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Pathology (AREA)
- Veterinary Medicine (AREA)
- Quality & Reliability (AREA)
- Signal Processing (AREA)
- Ophthalmology & Optometry (AREA)
- Human Computer Interaction (AREA)
- Closed-Circuit Television Systems (AREA)
- Studio Devices (AREA)
- Fittings On The Vehicle Exterior For Carrying Loads, And Devices For Holding Or Mounting Articles (AREA)
- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
- Image Analysis (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102022001262.6A DE102022001262A1 (de) | 2022-04-12 | 2022-04-12 | Innenraumüberwachungssystem und Verfahren zu dessen Betrieb sowie Fahrzeug mit einem solchen Innenraumüberwachungssystem |
| PCT/EP2023/058712 WO2023198498A1 (de) | 2022-04-12 | 2023-04-03 | Innenraumüberwachungssystem und verfahren zu dessen betrieb sowie fahrzeug mit einem solchen innenraumüberwachungssystem |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP4285341A1 true EP4285341A1 (de) | 2023-12-06 |
Family
ID=86095702
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP23718621.8A Withdrawn EP4285341A1 (de) | 2022-04-12 | 2023-04-03 | Innenraumüberwachungssystem und verfahren zu dessen betrieb sowie fahrzeug mit einem solchen innenraumüberwachungssystem |
Country Status (7)
| Country | Link |
|---|---|
| US (1) | US12506957B2 (de) |
| EP (1) | EP4285341A1 (de) |
| JP (1) | JP7795650B2 (de) |
| KR (1) | KR20240157046A (de) |
| CN (1) | CN118742927A (de) |
| DE (1) | DE102022001262A1 (de) |
| WO (1) | WO2023198498A1 (de) |
Family Cites Families (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6412813B1 (en) * | 1992-05-05 | 2002-07-02 | Automotive Technologies International Inc. | Method and system for detecting a child seat |
| JP2008053901A (ja) | 2006-08-23 | 2008-03-06 | Konica Minolta Holdings Inc | 撮像装置および撮像方法 |
| JP4372804B2 (ja) | 2007-05-09 | 2009-11-25 | トヨタ自動車株式会社 | 画像処理装置 |
| JP5177011B2 (ja) | 2009-02-25 | 2013-04-03 | 株式会社デンソー | 開眼度特定装置 |
| DE102011110486A1 (de) | 2011-08-17 | 2013-02-21 | Daimler Ag | Verfahren und Vorrichtung zur Überwachung zumindest eines Fahrzeuginsassen und Verfahren zum Betrieb zumindest einer Assistenzvorrichtung |
| DE102014200783B4 (de) | 2014-01-17 | 2025-12-04 | Bayerische Motoren Werke Aktiengesellschaft | Verfahren, Vorrichtung und Computerprogrammprodukt zum Betreiben eines Kraftfahrzeugs |
| US11669090B2 (en) * | 2014-05-20 | 2023-06-06 | State Farm Mutual Automobile Insurance Company | Autonomous vehicle operation feature monitoring and evaluation of effectiveness |
| DE102014014307A1 (de) * | 2014-09-25 | 2016-03-31 | Audi Ag | Verfahren zum Betrieb einer Mehrzahl von Radarsensoren in einem Kraftfahrzeug und Kraftfahrzeug |
| DE102014221039A1 (de) | 2014-10-16 | 2016-04-21 | Robert Bosch Gmbh | Steuergerät für ein Kraftfahrzeug mit Kamera für Fahrergesicht und Verfahren zum Aufnehmen des Gesichtes eines Fahrzeuginsassen |
| JP6443393B2 (ja) * | 2016-06-01 | 2018-12-26 | トヨタ自動車株式会社 | 行動認識装置,学習装置,並びに方法およびプログラム |
| US11845440B2 (en) * | 2017-08-02 | 2023-12-19 | Red Bend Ltd. | Contactless detection and monitoring system of vital signs of vehicle occupants |
| JP2020050077A (ja) | 2018-09-26 | 2020-04-02 | 株式会社Subaru | 車両の乗員監視装置、および乗員保護システム |
| DE102019001563A1 (de) | 2019-03-06 | 2019-09-05 | Daimler Ag | Verfahren zur Überwachung eines lnnenraumes |
| US11524691B2 (en) * | 2019-07-29 | 2022-12-13 | Lear Corporation | System and method for controlling an interior environmental condition in a vehicle |
| DE102019215691A1 (de) | 2019-10-11 | 2021-04-15 | Volkswagen Aktiengesellschaft | Verfahren und Vorrichtung zur Zustandserkennung eines Fahrzeuginsassen |
| US11978266B2 (en) * | 2020-10-21 | 2024-05-07 | Nvidia Corporation | Occupant attentiveness and cognitive load monitoring for autonomous and semi-autonomous driving applications |
-
2022
- 2022-04-12 DE DE102022001262.6A patent/DE102022001262A1/de active Pending
-
2023
- 2023-04-03 KR KR1020247031955A patent/KR20240157046A/ko active Pending
- 2023-04-03 EP EP23718621.8A patent/EP4285341A1/de not_active Withdrawn
- 2023-04-03 WO PCT/EP2023/058712 patent/WO2023198498A1/de not_active Ceased
- 2023-04-03 JP JP2024559218A patent/JP7795650B2/ja active Active
- 2023-04-03 US US18/856,322 patent/US12506957B2/en active Active
- 2023-04-03 CN CN202380022256.XA patent/CN118742927A/zh active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| JP7795650B2 (ja) | 2026-01-07 |
| WO2023198498A1 (de) | 2023-10-19 |
| DE102022001262A1 (de) | 2023-10-12 |
| US12506957B2 (en) | 2025-12-23 |
| CN118742927A (zh) | 2024-10-01 |
| KR20240157046A (ko) | 2024-10-31 |
| JP2025511762A (ja) | 2025-04-16 |
| US20250260894A1 (en) | 2025-08-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP3452317B1 (de) | Verfahren zum verbessern von lichtverhältnissen aus sicht eines fahrers eines kraftfahrzeugs | |
| DE102013100327B4 (de) | Fahrzeugfahrtumgebungserkennungsvorrichtung | |
| WO2003060826A1 (de) | Verfahren und vorrichtung zur erkennung von sichtbehinderungen bei bildsensorsystemen | |
| DE102022115813A1 (de) | Fahrzeug und steuerverfahren davon | |
| EP3655299B1 (de) | Verfahren und vorrichtung zum ermitteln eines optischen flusses anhand einer von einer kamera eines fahrzeugs aufgenommenen bildsequenz | |
| DE102004034532B4 (de) | Verfahren zur Kennzeichnung von Bildinformationen in der Darstellung eines mit einer fahrzeugseitigen Bildaufnahmeeinrichtung aufgenommenen Nachtsichtbildes und zugehöriges Nachtsichtsystem | |
| DE10302671A1 (de) | Verfahren und Vorrichtung zur Einstellung eines Bildsensorsystems | |
| DE102019218790A1 (de) | Verfahren zum Bereitstellen von Bilddaten von einem Kamerasystem sowie Kamerasystem und Kraftfahrzeug | |
| DE102022130104A1 (de) | Fahrzeugkameradynamik | |
| DE212013000187U1 (de) | System Abbildung einer Aussenszene durch Verwendung eines anwendungsspezifischen Bildsensors | |
| WO2024033123A2 (de) | Verfahren zum harmonisierten anzeigen von kamerabildern in einem kraftfahrzeug und entsprechend eingerichtetes kraftfahrzeug | |
| DE102005023697A1 (de) | Einrichtung zur Steuerung der Innenbeleuchtung eines Kraftfahrzeugs | |
| DE102019114904A1 (de) | Vorausschauende Erkennung einer Fahrbahnbeschaffenheit mittels eines Laserscanners und einer Kameraeinheit | |
| WO2023198498A1 (de) | Innenraumüberwachungssystem und verfahren zu dessen betrieb sowie fahrzeug mit einem solchen innenraumüberwachungssystem | |
| EP3934929B1 (de) | Verfahren zur klassifizierung von objekten innerhalb eines kraftfahrzeugs | |
| DE112017007253T5 (de) | Vorrichtung zur bestimmung des konzentrationsgrades, verfahren zur bestimmung des konzentrationsgrades und programm zur bestimmung des konzentrationsgrades | |
| DE102004047476B4 (de) | Vorrichtung und Verfahren zur Einstellung einer Kamera | |
| DE102020209275A1 (de) | Verfahren und System zum proaktiven Einstellen einer biometrischen Fahrzeuginsassen-Überwachungsvorrichtung in Bezug auf bevorstehende Straßenbedingungen | |
| DE102023005203A1 (de) | Verfahren zur Sensorfusion | |
| WO2019052936A1 (de) | Dynamisch kolorierte anzeige eines fahrzeugs | |
| DE102021205993A1 (de) | Verfahren zum Betreiben eines Scheinwerfersystems eines Kraftfahrzeugs | |
| DE102022115866A1 (de) | Verfahren zur robusten automatischen Anpassung von Head-Up-Displays | |
| DE102024208951B3 (de) | Verfahren zur Abstimmung eines teilautomatisierten Fahrassistenzsystems und Kraftfahrzeug zur Durchführung des Verfahrens | |
| DE102023002181B3 (de) | Adaptive Filterkette zum Anzeigen eines Umfeldmodells in einem Fahrzeug | |
| DE102024105312B4 (de) | Betriebsverfahren zum Betreiben einer Reinigungsanlage eines Fahrzeugs |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: UNKNOWN |
|
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE |
|
| 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 |
|
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE |
|
| 17P | Request for examination filed |
Effective date: 20230829 |
|
| AK | Designated contracting states |
Kind code of ref document: A1 Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC ME MK MT NL NO PL PT RO RS SE SI SK SM TR |
|
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: EXAMINATION IS IN PROGRESS |
|
| 17Q | First examination report despatched |
Effective date: 20250114 |
|
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: THE APPLICATION HAS BEEN WITHDRAWN |
|
| 18W | Application withdrawn |
Effective date: 20250512 |