Patent Description:
Any discussion of the background art throughout the specification should in no way be considered as an admission that such art is widely known or forms part of common general knowledge in the field.

In monitoring and surveillance systems, it is often necessary to monitor a scene from different perspectives. This is typically achieved by positioning multiple cameras at different positions and orientations throughout the scene. In some applications, it is advantageous to be able to track and map the positions of objects from the field of view of one camera to another. This is generally possible when the fields of view of the different cameras are overlapping or directly adjacent.

In vehicle and driver monitoring systems, the inventors have identified advantages in being able to map the gaze of the driver as viewed from a driver facing camera onto a forward facing road scene as viewed from a forward facing camera. To perform such a mapping procedure, it is necessary to know accurately the relative positions and orientations of each camera so that an accurate mapping or projection of the object position between each camera view can be performed. Unfortunately, the cameras in these systems have vastly different camera poses and do not have overlapping or adjacent fields of view.

<NPL>) is a study investigating eye-movement patterns and gaze behavior in bends in normal driving on a real road.

In accordance with a first aspect of the present invention there is provided a method of determining a camera pose of a forward facing camera in a vehicle scene, the method including:.

In one embodiment the reference points include a position of the road in front of the vehicle.

In some embodiments step d) includes determining a location of a road lane in front of the vehicle by processing the images captured by the forward facing camera. In one embodiment step d) includes determining an angle of gradient of the vehicle. In one embodiment step d) includes identifying the position of the driver's head within the vehicle cabin. The position of the driver's head may be identified by performing facial recognition on the driver and loading physiological data. In one embodiment a seat height, angle and/or lateral position of the driver's seat is determined.

In one embodiment step b)i. includes determining the orientation of the driver facing camera in the vehicle coordinate system using an orientation sensor.

In accordance with a second aspect of the present invention there is provided a vehicle monitoring system including: one or more driver facing cameras (<NUM>) positioned to capture images of a vehicle driver's face in the driver facing camera (<NUM>) frame of reference during normal operation of the vehicle (<NUM>) when the driver is seated in the driver's seat and operating the vehicle; a forward facing camera (<NUM>) positioned to capture images of a forward road scene in front of the vehicle in the forward facing camera (<NUM>) frame of reference during normal operation of the vehicle (<NUM>); a computer processor configured to perform a method according to the first aspect.

In accordance with a third aspect of the present invention there is provided a non-transitive carrier medium carrying computer executable code that, when executed on a processor, causes the processor to perform a method according to the first aspect.

In accordance with a fourth aspect of the present invention there is provided a computer program configured to perform a method according to the first aspect.

Preferred embodiments of the disclosure will now be described, by way of example only, with reference to the accompanying drawings in which:.

The embodiments of the present invention described herein relate to determining a camera pose of a forward facing camera in a multi-camera vehicle monitoring system. In these embodiments, the scene to be imaged includes a driver of a vehicle, the interior of the vehicle/cockpit, the forward road scene of the vehicle and optionally side and rear views from the vehicle. The vehicle may represent a commercial automobile, truck, earthmoving machine, airplane, jet or helicopter. However, it will be appreciated that the invention is applicable to other multi-camera monitoring systems.

Use of the term camera pose herein represents a three dimensional position and three dimensional orientation of a camera within a scene.

Referring initially to <FIG> and <FIG>, there is illustrated a vehicle monitoring system <NUM> including four cameras <NUM>-<NUM> disposed at different locations within a vehicle <NUM>. Camera <NUM> is positioned on a dashboard of the vehicle and oriented in a forward direction of the vehicle for monitoring the forward road scene. Cameras <NUM>, <NUM> and <NUM> are positioned and oriented to monitor a driver <NUM> of vehicle <NUM>. Camera <NUM> is positioned on or adjacent an instrument panel of vehicle <NUM> or on the steering column of vehicle <NUM>. Camera <NUM> is positioned on the driver side A-pillar of the frame of vehicle <NUM>. Camera <NUM> is positioned on or adjacent a center console of vehicle <NUM>, preferably adjacent a display screen in vehicles where such a screen is provided. The specific camera locations are exemplary only and it will be appreciated that more or less cameras can be incorporated at other locations within or outside vehicle <NUM> to monitor the driver, the forward road scene or other views in or around the vehicle. Other exemplary camera locations of cameras include a rearview mirror, rear bumper, front bumper, vehicle roof and bonnet/hood.

Referring now to <FIG>, there is illustrated a system level diagram of system <NUM>. System <NUM> includes a central processing unit <NUM> including a processor <NUM>, memory <NUM>, a power source <NUM>, a network interface <NUM> and a user input device <NUM>. In the embodiments of a vehicle monitoring system, central processing unit <NUM> is preferably mounted within the vehicle dash or center console and can be integrated with an onboard vehicle computer system during manufacture. However, central processing unit <NUM> and system <NUM> as a whole may be manufactured as an after-market product and subsequently installed into vehicle in a modular manner.

Processor <NUM> may represent a conventional microprocessor or personal computer having hardware and/or software configured for processing image streams received from multiple cameras. By way of example, processor <NUM> may include system-on-chip technology and include a video processing pipeline for processing the stream of images from cameras <NUM>-<NUM>. In one embodiment, processor <NUM> is integral with or in communication with a processor of an onboard vehicle computer system.

Central processing unit <NUM> is powered by connection to a power source <NUM>. In one embodiment, power source <NUM> represents an electrical connection to a vehicle power source such as the vehicle battery. In another embodiment, power source <NUM> represents a local battery integrated within a housing of central processing unit <NUM> and optionally connected to an external power source for recharging.

Network interface <NUM> provides for communicating data to and from system <NUM> and represents an electrical or wireless interface for connecting system <NUM> to other devices or systems. Network interface <NUM> includes wired network ports such as USB, HDMI or Ethernet ports, serial device ports and/or wireless devices such as a Bluetooth™ device, Wi-Fi™ device or cellular network transceiver.

User input is able to be provided to system <NUM> through user input device <NUM>, which can include a touchscreen display or a keyboard or keypad and associated display. User input device <NUM> may also represent external devices such as computers or smartphones connected to system <NUM> through network interface <NUM> or other means. In one embodiment, user input device <NUM> represents a computer system integrated into the vehicle and manipulated through a display interface mounted in the vehicle's center console.

Example data that can be input to system <NUM> through user input device <NUM> includes:.

Example data that can be extracted from system <NUM> through user input device <NUM> includes:.

System <NUM> includes four camera units <NUM>-<NUM>, which are mounted at relative locations within or about the scene to be monitored. Each camera unit <NUM>-<NUM> includes a respective camera <NUM>-<NUM> for capturing images of the scene within its respective field of view.

Each camera is electrically connected to central processing unit <NUM> through respective connections <NUM>-<NUM> including electrical cables and associated electrical ports. The electrical connections provide for control of cameras <NUM>-<NUM> by processor <NUM> and transmission of image data from cameras <NUM>-<NUM>.

Cameras <NUM>-<NUM> may utilize various types of known image sensors in combination with imaging optics. Example image sensors include charge-coupled devices (CCDs) or complementary metal-oxide-semiconductor (CMOS) chips combined with relevant processing electronics and memory to capture images and/or video sequences in suitable formats for subsequent image processing. Cameras <NUM>-<NUM> may be capable of capturing images in two or three dimensions.

In the vehicle scene, the frame of reference may be defined relative to a region of the vehicle frame. By way of example, a reference coordinate system may be defined as having a z-axis aligned along the vehicle drive shaft (longitudinal dimension), an x-axis aligned along the front wheel axle (defining a transverse dimension) with the right wheel being in the positive direction and a y-axis defining a generally vertical dimension to complete the orthogonal coordinate system. This exemplary coordinate system will be used herein to describe the invention. However, it will be appreciated that other arbitrary reference coordinate systems may be chosen.

An alternative embodiment system <NUM> is illustrated in <FIG>. Here corresponding features of system <NUM> are designated with the same reference numerals. System <NUM> includes four camera units <NUM>-<NUM>, which are mounted at relative locations within or about the vehicle scene. Each camera unit <NUM>-<NUM> includes not only respective cameras <NUM>-<NUM> but also respective orientation sensors <NUM>-<NUM> for measuring the orientation of the associated camera relative to a reference orientation.

Orientation sensors <NUM>-<NUM> may include simple inertial devices such as accelerometers and gyroscopes and other devices such as magnetometers and more advanced inertial measurement units, or combinations thereof. Orientation sensors <NUM>-<NUM> may be capable of measuring orientation in one, two or three dimensions relative to a reference orientation. A suitable reference orientation is that described above using the vehicle drive shaft and front wheel axle. However, it will be appreciated that a reference orientation can be chosen arbitrarily based on the particular application. For example, if two or more cameras were aligned along a common axis, that axis may be preferred as the reference orientation. The orientations are preferably expressed in a three dimensional Cartesian coordinate system. However, it will be appreciated that the orientations can be expressed in any arbitrary coordinate system such as a spherical coordinate system wherein an orientation vector is expressed in terms of a radial distance (r), a zenith angle (θ) in a vertical plane and an azimuthal angle (φ) in a horizontal plane.

In one embodiment, the orientation sensors <NUM>-<NUM> are mounted integrally on respective cameras <NUM>-<NUM>. In another embodiment, orientation sensors <NUM>-<NUM> are mounted relative to each camera <NUM>-<NUM> on an intermediate support frame on which the camera is also mounted.

Various types of camera mounts and actuators are able to be used in the present invention, including but not limited to C-type or T-type screw threaded mounts, hydraulic actuator mounts, thermal or magnetic actuator mounts and piezoelectric actuator mounts.

Monitoring system <NUM> preferably also includes one or more LEDs (not illustrated) for illuminating driver <NUM> to improve the quality of the captured images. To reduce distraction to the driver, the LEDs preferably emit infrared radiation that is invisible to the human eye. Thus, the image sensors of cameras <NUM>-<NUM> are preferably capable of imaging in the infrared region to leverage the illumination by the LEDs.

Initially, the cameras are installed in their desired locations within the scene to be monitored and their respective positions and initial orientations are registered in memory <NUM> through user input device <NUM>. The cameras are preferably mounted at locations in or around the vehicle such as those in <FIG> and <FIG> so as to position the driver and the forward road scene within their respective fields of view. Camera installation may be performed during manufacture of the vehicle or during a subsequent installation of systems <NUM> or <NUM> in vehicle <NUM>.

The initial position/orientation registration may be performed manually or in a quasi-automated manner utilizing orientation sensors <NUM>-<NUM> and a depth imaging device <NUM> as described in <CIT>. The contents of <CIT> are incorporated herein by way of cross reference. Depth imaging device <NUM> can include one or more of a scanning or pulsed time of flight camera, LIDAR system, stereoscopic camera arrangement, structured light 3D scanner, image sensor with phase detection or any other imaging system capable of capturing images of a scene in three dimensions. Depth imaging device <NUM> is operatively associated with processor <NUM> through a dedicated electrical connection to provide control to device <NUM> and receive raw three dimensional image data or pre-processed depth map data from device <NUM>. In some embodiments depth imaging device <NUM> is connected to central processing unit <NUM> and processor <NUM> through network interface <NUM>.

During the installation of the camera units <NUM>-<NUM>, each unit is electrically connected to central processing unit <NUM> through respective connections <NUM>-<NUM>. The frame of reference within the scene, such as those described above, is also defined. It is preferable that the reference orientation is defined by the scene geometry such that it remains constant over time.

The vehicle frame of reference is used as the central reference frame (or world reference) from which all measurements within system <NUM> will be taken. However, the cameras must first be calibrated to that frame of reference from their own frame of reference.

The operation of system <NUM> (and system <NUM>) for determining a camera pose of a forward facing camera (camera <NUM>) in a vehicle scene will be described with reference to method <NUM> illustrated in the flow chart of <FIG>.

At step <NUM>, images of a vehicle driver's face are captured from driver facing camera <NUM> in that camera's local frame of reference. Also images of the forward road scene are captured from forward facing camera <NUM> in that camera's frame of reference. These images are captured during normal operation of the vehicle when the driver is seated in the driver's seat and the vehicle is travelling along roads. The captured images are stored in memory <NUM> for processing by processor <NUM>.

At step <NUM>, the images of the driver's face from driver facing camera <NUM> are processed to derive gaze direction data in a vehicle frame of reference. This can be performed by a number of methods known in the art such as in <CIT> entitled "Facial Image Processing System", which is assigned to Seeing Machines Pty Ltd. The contents of <CIT>.

The derived gaze direction data is initially expressed as two or three dimensional coordinates in the frame of reference of camera <NUM>. To convert the gaze direction data into the vehicle frame of reference for use by other cameras, a transformation of the camera pose of camera <NUM> into the vehicle frame of reference is required. In one embodiment, this is achieved by capturing one or more images of the vehicle scene from the driver facing camera <NUM> and comparing the one or more images of the vehicle scene to reference information about the vehicle scene. In one embodiment, the reference information includes an earlier captured image by the camera at a known camera pose in the vehicle frame of reference. In another embodiment, the reference information includes a three dimensional model of the vehicle cabin, such as a CAD model of the vehicle design. The reference information includes two or three dimensional positions of known objects or regions within the vehicle scene such as dashboard instruments, cabin contours and edges or the entire cabin itself in the case of a three dimensional CAD model. The comparison may include performing pattern matching of the known objects or regions within the scene, as seen in both the captured images and the reference information. The comparison may also include an estimation based on a machine learning process such as a neural network having previously learned the structure of the vehicle scene.

Once the gaze direction data is calculated in the vehicle frame of reference, at step <NUM>, the gaze direction data is statistically collated into a frequency distribution of gaze angles. This may include performing a statistical analysis on the gathered data over a statistically significant period of time. For example, system <NUM> makes use of historical gaze direction data stored in memory <NUM> in a manner similar to that described in <CIT> entitled "Automatic Calibration of a Gaze Direction Algorithm from User Behavior", which is assigned to Seeing Machines Limited. The contents of <CIT>. This technique involves using known reference points within the scene to calibrate gaze coordinates with the scene geometry.

The historical gaze direction data are collated statistically to form a frequency distribution of gaze angles such as in a one or two dimensional histogram having bins of gaze position or angle. An example one dimensional gaze direction histogram is illustrated in <FIG>. A similar histogram could be obtained for the orthogonal direction.

At step <NUM>, the statistical data are analyzed to identify one or more peaks in the frequency distribution. Identified peaks are associated with corresponding reference points in the images of the forward road scene from forward facing camera <NUM>. This association allows the determination of reference gaze positions in the vehicle reference frame. For mapping the gaze onto images of the forward facing camera <NUM>, the reference points must lie within the field of view of camera <NUM> to be useful.

The peaks in the gaze histogram represent points more commonly regarded and these can be calibrated against known objects or reference points within the scene with which the driver is likely to observe. Example objects or reference points within the vehicle cabin include a vehicle center console, the vehicle dash instrument panel, the driver's lap, the left and right reversing mirrors and the rearview mirror. However, these objects do not typically lie in the field of view of the forward facing camera <NUM>. For the purpose of mapping the gaze to the images of the forward facing camera <NUM>, the center of the lane in front of the vehicle typically represents the most commonly viewed reference point within the field of view of camera <NUM>. The center of the lane represents a center of optical flow indicating the default eye gaze position on the forward road scene that the driver views during normal vehicle operation. This will typically reflect a point roughly in the center of the current lane in which the vehicle is travelling at a distance of <NUM> meters to <NUM> meters in front of the vehicle. Thus, it will have the largest peak in a driver gaze histogram.

As the center of the lane is a variable region, a large amount of statistical data should be used to more precisely locate this region. Further, as this region varies horizontally with road curvature and vertically with road gradient, system <NUM> may leverage additional data to account for these variations. By way of example, system <NUM> may determine a location of a road lane in front of the vehicle by processing the images captured by forward facing camera <NUM>. Identification of the lane markings can determine horizontal boundaries within which the driver's gaze is likely to lie. Additionally, leveraging angle of gradient of the vehicle due to road gradient by an on-board vehicle orientation sensor can be used to more accurately identify likely gaze position in the forward road scene.

Accordingly, it is possible to accurately determine a two or three dimensional region, within the images captured by forward facing camera <NUM>, which corresponds to the peak in the gaze direction histogram. The size of the region of the forward road scene is dependent on the amount and type of data used. In one embodiment, a machine learning process such as a neural network is fed the gaze direction data (in the vehicle frame of reference), lane position data and vehicle gradient data to learn patterns of gaze behaviour.

During periods where the driver gaze is highly likely to be looking at the center of the lane position (or another reference point), at step <NUM>, reference gaze position (peak in the gaze histogram) is correlated with a determined position of the center lane position. That is, the largest peak in the gaze histogram is correlated with the gaze direction data by specifying that gaze position with the estimated three dimensional position of the point of regard on the road. This allows the correlation of a point in the frame of reference of the forward facing camera <NUM> with a point in the vehicle frame of reference, as captured by the driver facing camera <NUM>. Thus, a camera pose of forward facing camera <NUM> in the vehicle frame of reference can be determined. This process can be repeated over time to more accurately calibrate the camera pose of camera <NUM> with the vehicle frame of reference.

Thus, by estimating the position of the center of the forward road lane (or other object/region statistically definable by gaze definable), the gaze direction calculated form images of the driver's face captured from one of cameras <NUM>-<NUM> can be accurately mapped to the forward facing road scene captured by camera <NUM>. The projection or mapping may be performed by deriving a transformation function or matrix which maps the gaze direction observed in the driver facing camera onto the forward facing road scene images captured from the forward facing camera. In some embodiments, the calibration may be performed with multiple histogram peaks indicating a plurality of known reference objects or points.

As the peak in the gaze histogram is dependent on the origin of the driver's eyes, this calibration technique is dependent upon the physiology of the driver (having different head heights etc). In some embodiments, face recognition can be used to register the driver and load past gaze direction data or a predetermined gaze histogram. This may optionally be augmented with the current seat height, angle and lateral positions settings for additional accuracy.

It will be appreciated that the system and method described above provides for efficiently and accurately determining a camera pose of a forward facing camera in a multi-camera vehicle system. This allows the camera pose of a forward facing camera to be determined in a common vehicle reference frame using gaze direction data from the vehicle driver. From this, the driver's eye gaze direction captured from a driver facing camera can be projected onto images of a forward facing camera to indicate a point of regard of the driver during vehicle operation.

Unless specifically stated otherwise, as apparent from the following discussions, it is appreciated that throughout the specification discussions utilizing terms such as "processing," "computing," "calculating," "determining", analyzing" or the like, refer to the action and/or processes of a computer or computing system, or similar electronic computing device, that manipulate and/or transform data represented as physical, such as electronic, quantities into other data similarly represented as physical quantities.

In a similar manner, the term "controller" or "processor" may refer to any device or portion of a device that processes electronic data, e.g., from registers and/or memory to transform that electronic data into other electronic data that, e.g., may be stored in registers and/or memory.

The methodologies described herein are, in one embodiment, performable by one or more processors that accept computer-readable (also called machine-readable) code containing a set of instructions that when executed by one or more of the processors carry out at least one of the methods described herein. Any processor capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken are included. Thus, one example is a typical processing system that includes one or more processors. Each processor may include one or more of a CPU, a graphics processing unit, and a programmable DSP unit. The processing system further may include a memory subsystem including main RAM and/or a static RAM, and/or ROM. A bus subsystem may be included for communicating between the components. The processing system further may be a distributed processing system with processors coupled by a network. If the processing system requires a display, such a display may be included, e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT) display. If manual data entry is required, the processing system also includes an input device such as one or more of an alphanumeric input unit such as a keyboard, a pointing control device such as a mouse, and so forth. The term memory unit as used herein, if clear from the context and unless explicitly stated otherwise, also encompasses a storage system such as a disk drive unit. The processing system in some configurations may include a sound output device, and a network interface device. The memory subsystem thus includes a computer-readable carrier medium that carries computer-readable code (e.g., software) including a set of instructions to cause performing, when executed by one or more processors, one of more of the methods described herein. Note that when the method includes several elements, e.g., several steps, no ordering of such elements is implied, unless specifically stated. The software may reside in the hard disk, or may also reside, completely or at least partially, within the RAM and/or within the processor during execution thereof by the computer system. Thus, the memory and the processor also constitute computer-readable carrier medium carrying computer-readable code.

Furthermore, a computer-readable carrier medium may form, or be included in a computer program product.

In alternative embodiments, the one or more processors operate as a standalone device or may be connected, e.g., networked to other processor(s), in a networked deployment, the one or more processors may operate in the capacity of a server or a user machine in server-user network environment, or as a peer machine in a peer-to-peer or distributed network environment. The one or more processors may form a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine.

Note that while diagrams only show a single processor and a single memory that carries the computer-readable code, those in the art will understand that many of the components described above are included, but not explicitly shown or described in order not to obscure the inventive aspect. For example, while only a single machine is illustrated, the term "machine" shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.

Thus, one embodiment of each of the methods described herein is in the form of a computer-readable carrier medium carrying a set of instructions, e.g., a computer program that is for execution on one or more processors, e.g., one or more processors that are part of web server arrangement. Thus, as will be appreciated by those skilled in the art, embodiments of the present invention may be embodied as a method, an apparatus such as a special purpose apparatus, an apparatus such as a data processing system, or a computer-readable carrier medium, e.g., a computer program product. The computer-readable carrier medium carries computer readable code including a set of instructions that when executed on one or more processors cause the processor or processors to implement a method. Accordingly, aspects of the present invention may take the form of a method, an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of carrier medium (e.g., a computer program product on a computer-readable storage medium) carrying computer-readable program code embodied in the medium.

The software may further be transmitted or received over a network via a network interface device. While the carrier medium is shown in an exemplary embodiment to be a single medium, the term "carrier medium" should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term "carrier medium" shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by one or more of the processors and that cause the one or more processors to perform any one or more of the methodologies of the present invention. A carrier medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, optical, magnetic disks, and magneto-optical disks. Volatile media includes dynamic memory, such as main memory. Transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise a bus subsystem. Transmission media also may also take the form of acoustic or light waves, such as those generated during radio wave and infrared data communications. For example, the term "carrier medium" shall accordingly be taken to included, but not be limited to, solid-state memories, a computer product embodied in optical and magnetic media; a medium bearing a propagated signal detectable by at least one processor of one or more processors and representing a set of instructions that, when executed, implement a method; and a transmission medium in a network bearing a propagated signal detectable by at least one processor of the one or more processors and representing the set of instructions.

It will be understood that the steps of methods discussed are performed in one embodiment by an appropriate processor (or processors) of a processing (i.e., computer) system executing instructions (computer-readable code) stored in storage. It will also be understood that the invention is not limited to any particular implementation or programming technique and that the invention may be implemented using any appropriate techniques for implementing the functionality described herein. The invention is not limited to any particular programming language or operating system.

Reference throughout this specification to "one embodiment", "some embodiments" or "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, appearances of the phrases "in one embodiment", "in some embodiments" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment.

As used herein, unless otherwise specified the use of the ordinal adjectives "first", "second", "third", etc., to describe a common object, merely indicate that different instances of like objects are being referred to, and are not intended to imply that the objects so described must be in a given sequence, either temporally, spatially, in ranking, or in any other manner.

It should be appreciated that in the above description of exemplary embodiments of the disclosure, various features of the disclosure are sometimes grouped together in a single embodiment, Figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claims require more features than are expressly recited in each claim. Thus, the claims following the Detailed Description are hereby expressly incorporated into this Detailed Description, with each claim standing on its own as a separate embodiment of this disclosure.

However, it is understood that embodiments of the disclosure may be practiced without these specific details.

Claim 1:
A method of determining a camera pose of a forward facing camera (<NUM>) in a vehicle scene, the method including:
a) capturing (<NUM>) images of a vehicle driver's face from a driver facing camera (<NUM>) in the driver facing camera (<NUM>) frame of reference and images of the forward road scene from a forward facing camera (<NUM>) in the forward facing camera (<NUM>) frame of reference during normal operation of the vehicle (<NUM>) when the driver is seated in the driver's seat and operating the vehicle;
b) processing (<NUM>) the images of the driver's face from the driver facing camera (<NUM>) to derive gaze direction data in a vehicle frame of reference;
c) statistically collating (<NUM>) the gaze direction data into a frequency distribution of gaze angles;
d) identifying (<NUM>) one or more peaks in the frequency distribution and associating the one or more peaks with a corresponding one or more reference points in the images of the forward road scene from the forward facing camera (<NUM>) to determine one or more reference gaze points of regard in the vehicle reference frame; and
e) correlating (<NUM>) the one or more reference gaze points of regard with a position of the reference points in the forward facing camera reference frame to map the gaze direction data to the images of the forward facing road scene to determine a camera pose of the forward facing camera (<NUM>) in the vehicle frame of reference so that driver's eye gaze direction captured from the driver facing camera (<NUM>) is projectable onto images of the forward facing camera (<NUM>) to indicate a point of regard of the driver during vehicle operation.