Patent Description:
Current contactless monitoring solutions utilize visual and thermal imagery for the measurement of body temperature and other medical indicators in order to help detect individuals that may be sick.

These current contactless monitoring systems require highly accurate and expensive sensors or to compromise on worse performances using low cost sensors. Therefore, current low-cost systems are not easily adapted to operate in changing environmental conditions.

There is thus a need in the art for a new body parameters measurement system and method.

References considered to be relevant as background to the presently disclosed subject matter are listed below. Acknowledgement of the references herein is not to be inferred as meaning that these are in any way relevant to the patentability of the presently disclosed subject matter.

WIPO International application No.<CIT>, discloses a physiological monitoring apparatus (<NUM>) and methods are disclosed. A physiological monitor includes imaging sensors (<NUM>, <NUM>, <NUM>, <NUM>), one of which is a time-of-flight imaging sensor (<NUM>). The physiological monitor (<NUM>) also includes a processing device (<NUM>) to receive data streams from the imaging sensors (<NUM>, <NUM>, <NUM>, <NUM>). The processing device (<NUM>) may then extract time parameter data from the data streams, identify a physiological parameter from the extracted parameter data, and provide an indication of the physiological parameter.

<NPL>, discloses how facial biometrics, acquired using multi-spectral sensors, such as RGB, depth, and infrared, assist the data accumulation in the process of authorizing users of automated and semi-automated access systems. This data serves the purposes of person authentication, as well as facial temperature estimation. We utilize depth data taken using an inexpensive RGB-D sensor to find the head pose of a subject. This allows the selection of video frames containing a frontal-view head pose for face recognition and face temperature reading. Usage of the frontal-view frames improves the efficiency of face recognition while the corresponding synchronized IR video frames allow for more efficient temperature estimation for facial regions of interest.

WIPO International application No. <CIT>, discloses a tracking system comprising one or more cameras adapted to take images, one or more data processing units, said tracking system further comprising one or more output or display units, wherein said camera is adapted to observe a geographical area of interest, wherein said one or more data processing unit is configured to detect a moving entity in the area of interest, to identify a reference zone in at least some of said images, wherein said reference zone is on or associated with said moving entity, and to analyze the reference zone in order to determine at least one parameter associated with said moving entity.

<CIT>, discloses apparatuses and techniques for radar-enabled sensor fusion. In some aspects, a radar field is provided and reflection signals that correspond to a target in the radar field are received. The reflection signals are transformed to provide radar data, from which a radar feature indicating a physical characteristic of the target is extracted. Based on the radar features, a sensor is activated to provide supplemental sensor data associated with the physical characteristic. The radar feature is then augmented with the supplemental sensor data to enhance the radar feature, such as by increasing an accuracy or resolution of the radar feature. By so doing, performance of sensor-based applications, which rely on the enhanced radar features, can be improved.

<CIT>, discloses intelligent assistant devices and methods for interacting with a user are disclosed. In some examples, a method for interacting with a user comprises predicting suggested action(s) for the user and displaying the action(s) via a display of the device. While the suggested action(s) are displayed, audio input comprising a command followed by a keyword is received from the user. The audio input is processed locally on the intelligent assistance device to (<NUM>) determine that the keyword follows the command and (<NUM>) recognize that the command applies to the suggested action(s). Based on determining that the keyword follows the command and recognizing that the command applies to the suggested action(s), a user selection of the suggested action(s) is established. Based on establishing the user selection, the one or more suggested actions are executed.

<CIT>, discloses a passive-tracking system is described herein. The system can include a visible-light sensor, a sound transducer, a thermal sensor, a time-of-flight (ToF) sensor, and a processor. The processor can receive visible-light frames from the visible-light sensor, sound frames from the sound transducer, thermal frames from the thermal sensor, and modulated-light frames from the ToF sensor. The processor, based on data of the visible-light and temperature frames, can also determine that an object is a living being and can provide an X and Y position of the object. The processor, based on data of the sound and positioning frames, can determine a Z position of the object. The X, Y, and Z positions may combine to form a three-dimensional (3D) position of the object. The processor can also passively track the object over time by selectively updating the 3D position of the object.

Document <CIT> discloses an imaging system including a 3D image capture device, which is configured to capture a depth image of an object, and a thermal image capture device, which is configured to capture a thermal image of the object. The imaging system also includes a processing system, which is coupled with the 3D image capture device and the thermal image capture device. The processing system is configured to process the depth image and the thermal image to produce a thermal-depth fusion image by aligning the thermal image with the depth image, and assigning a thermal value derived from the thermal image to a plurality of points of the depth image.

Document <CIT> relates to a dual camera-based body temperature monitoring system using a blackbody, capable of measuring the temperature of a person while recording an image of the measured person by simultaneously photographing the person with a thermo-graphic camera and a visible ray camera.

Document <CIT> relates to a body temperature tracking monitoring system using a dual camera that captures a person at the same time by using a thermal camera and a visible light camera, and measures a body temperature of a person and records an image of a person who has measured the same.

Document <CIT> discloses a system for fast noncontact screening for fever human subjects by means of a thermal imaging camera. The camera is combined with a target gate that incorporates the reference blackbody targets and position detectors to identify the temperature scale and size of a subject.

Document <CIT> relates to a method for enabling improved calibration of captured infrared data values by an IR imaging system in a thermography arrangement dependent on an infrared (IR) image depicting an observed real world scene, said IR image being captured by a thermography arrangement comprising said IR imaging system, wherein infrared (IR) image is related to temperature dependent on IR calibration parameters, the method comprising: capturing an IR image depicting the observed real world scene using the IR imaging system, determining that a predefined feature is represented by IR pixels in the IR image and obtaining a second subset of said IR pixels representing said predefined feature; and calibrating said IR imaging system based on the captured infrared data values associated with said second subset of said IR pixels and a predetermined temperature value associated to said predefined feature.

Document <CIT> discloses systems and methods for mobile and augmented reality-based depth and thermal fusion scan imaging.

In accordance with a first aspect of the presently disclosed subject matter, there is provided a system for measuring temperature of at least two subjects within a scene including a reference object, the reference object having an unknown emissivity and an ambient temperature, wherein the ambient temperature of the reference object is the scene ambient temperature, the system comprising: a visible spectrum camera configured to acquire images of the scene comprising (a) at least a Region of Interest (RoI) of each of the subjects, and (b) the reference object; a thermal image sensor configured to acquire images of the scene comprising (a) at least the RoI of each of the subjects, and (b) the reference object; and a processing circuitry configured to: obtain (a) a visible spectrum image captured by the visible spectrum camera, and (b) a thermal image captured by the thermal image sensor, and (c) an indication of the scene ambient temperature within the scene; register the visible spectrum image and the thermal image onto a common coordinate system; identify (a) RoI pixels, on the common coordinate system, of the RoIs of the subjects within the visible spectrum image, and (b) reference object pixels, on the common coordinate system, of the reference object within the visible spectrum image; determine (a) RoI temperatures of the RoIs of the subjects by analyzing the identified RoI pixels on the thermal image, (b) a reference temperature by analyzing the reference object pixels on the thermal image, and (c) a parameter correlated to an emissivity of the reference object, based on the reference temperature and on the indication of the scene ambient temperature; and upon existence of a difference between the reference temperature and the indication of the scene ambient temperature, correct the RoI temperatures, based on the difference and utilizing the parameter, to compensate for the difference, giving rise to corrected RoI temperatures.

In some cases, the determination of the parameter correlated to the emissivity of the reference object is performed by analyzing the reference temperature and the indication of the scene ambient temperature at a plurality of point in time during a given time period.

In some cases, the system further comprising a three-dimensional (3D) camera capable of acquiring images of the scene comprising (a) at least a Region of Interest (RoI) of each of the subjects, and (b) the reference object, and wherein the processing circuitry is further configured to: obtain a depth image captured by the 3D camera; and utilize the depth image for the registration of the visible spectrum image and the thermal image onto the common coordinate system.

In some cases, the correction of the RoI temperatures is also based on at least one of: (a) a distance of the respective subject from the thermal image sensor determined based on the analysis of the depth image, or (b) on ambient moisture level.

In some cases, the indication of the ambient moisture level of is obtained from a moisture measuring device.

In some cases, the indication of the scene ambient temperature is obtained from a thermometer measuring ambient temperature within the scene.

In some cases, the thermal image sensor is uncooled.

In some cases, the visible spectrum camera has a spatial resolution higher than <NUM>/pixel.

In some cases, the thermal spectrum camera has a spatial resolution higher than <NUM>/pixel.

In some cases, the subjects are living subjects.

In some cases, the RoI is a body part of a body of the subject.

In some cases, the subjects are animals and wherein the RoI is one or more of: a body part of a body of the respective animal subject, a face of the respective animal subject, a forehead of the respective animal subject, or a mouth of the respective animal subject.

In some cases, the animals are human beings.

In some cases, the subjects are plants and wherein the RoI is one or more of: a leaf of the respective plant subject, or a fruit of the respective plant subject.

In some cases, the subjects are machines and wherein the RoI is an engine of the respective machine subject.

In some cases, the reference object is diffusive and not specular.

In some cases, the processing circuitry is further configured to alert an operator of the system upon identifying subjects associated with corrected RoI temperatures exceeding a threshold.

In some cases, the reference object is made of material which temperature changes in a known manner according to changes to the scene ambient temperature.

In some cases, the RoI is an area affected by breathing of the respective subject and wherein the processing circuitry is further configured to:obtain (a) a first sequence of subsequent visible spectrum images captured by the visible spectrum camera subsequently to the visible spectrum image, and (b) a second sequence of subsequent thermal images captured by the thermal image sensor subsequently to the thermal image; register the subsequent visible spectrum images and the subsequent thermal images onto the common coordinate system; identify subsequent RoI pixels, on the common coordinate system, of the RoIs of the subjects within the subsequent visible spectrum images; track the subsequent RoI pixels within the subsequent thermal images of the second sequence utilizing the respective subsequent visible spectrum images of the first sequence; and determine a respiratory rate of the respective subject by analyzing the tracked subsequent RoI pixels.

In some cases, the RoI is a forehead of the respective subject and wherein the processing circuitry is further configured to: obtain a third sequence of subsequent visible spectrum images captured by the visible spectrum camera subsequently to the visible spectrum image; track the RoI within the subsequent visible spectrum images of the third sequence; and determine a pulse of the respective subject by analyzing changes of color within the RoI.

In some cases, the reference object includes one or more symbols visible to the visible spectrum camera or to the thermal image sensor and wherein the reference object pixels are identified using at least one of the symbols.

In accordance with a second aspect of the presently disclosed subject matter, there is provided a method for measuring temperature of at least two subjects within a scene including a reference object, the reference object having an unknown emissivity and an ambient temperature, wherein the ambient temperature of the reference object is the scene ambient temperature, the method comprising: obtaining, by a processing circuitry, (a) a visible spectrum image captured by a visible spectrum camera configured to acquire images of the scene comprising at least a Region of Interest (RoI) of each of the subjects, and the reference object, and (b) a thermal image captured by a thermal image sensor configured to acquire images of the scene comprising at least the RoI of each of the subjects, and the reference object, and (c) an indication of the scene ambient temperature within the scene; registering, by the processing circuitry, the visible spectrum image and the thermal image onto a common coordinate system; identifying, by the processing circuitry, (a) RoI pixels, on the common coordinate system, of the RoIs of the subjects within the visible spectrum image, and (b) reference object pixels, on the common coordinate system, of the reference object within the visible spectrum image; determining, by the processing circuitry, (a) RoI temperatures of the RoIs of the subjects, by analyzing the identified RoI pixels on the thermal image, (b) a reference temperature by analyzing the reference object pixels on the thermal image and (c) a parameter correlated to an emissivity of the reference object, based on the reference temperature and on the indication of the scene ambient temperature; and upon existence of a difference between the reference temperature and the indication of the scene ambient temperature, correcting, by the processing circuitry, the RoI temperatures, based on the difference and utilizing the parameter, to compensate for the difference, giving rise to corrected RoI temperatures.

In some cases, the method further comprising: obtaining, by the processing circuitry, a depth image captured by a three-dimensional (3D) camera capable of acquiring images of the scene comprising (a) at least a Region of Interest (RoI) of each of the subjects, and (b) the reference object; and utilizing, by the processing circuitry, the depth image for the registration of the visible spectrum image and the thermal image onto the common coordinate system.

In some cases, the method further comprising alerting, by the processing circuitry, an operator of the system upon identifying subjects associated with corrected RoI temperatures exceeding a threshold.

In some cases, the RoI is an area affected by breathing of the respective subject and wherein method further comprising: obtaining, by the processing circuitry, (a) a first sequence of subsequent visible spectrum images captured by the visible spectrum camera subsequently to the visible spectrum image, and (b) a second sequence of subsequent thermal images captured by the thermal image sensor subsequently to the thermal image; registering, by the processing circuitry, the subsequent visible spectrum images and the subsequent thermal images onto the common coordinate system; identifying, by the processing circuitry, subsequent RoI pixels, on the common coordinate system, of the RoIs of the subjects within the subsequent visible spectrum images; tracking, by the processing circuitry, the subsequent RoI pixels within the subsequent thermal images of the second sequence utilizing the respective subsequent visible spectrum images of the first sequence; and determining, by the processing circuitry, a respiratory rate of the respective subject by analyzing the tracked subsequent RoI pixels.

In some cases, the RoI is a forehead of the respective subject and wherein the method further comprising: obtaining, by the processing circuitry, a third sequence of subsequent visible spectrum images captured by the visible spectrum camera subsequently to the visible spectrum image; tracking, by the processing circuitry, the RoI within the subsequent visible spectrum images of the third sequence; and determining, by the processing circuitry, a pulse of the respective subject by analyzing changes of color within the RoI.

In accordance with a third aspect of the presently disclosed subject matter, there is provided a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, executable by at least one processing circuitry of a computer to perform a method for measuring temperature of at least two subjects within a scene including a reference object, the reference object having an unknown emissivity and an ambient temperature, wherein the ambient temperature of the reference object is the scene ambient temperature, the method comprising: obtaining, by a processing circuitry, (a) a visible spectrum image captured by a visible spectrum camera configured to acquire images of the scene comprising at least a Region of Interest (RoI) of each of the subjects, and the reference object, and (b) a thermal image captured by a thermal image sensor configured to acquire images of the scene comprising at least the RoI of each of the subjects, and the reference object, and (c) an indication of the scene ambient temperature within the scene; registering, by the processing circuitry, the visible spectrum image and the thermal image onto a common coordinate system; identifying, by the processing circuitry, (a) RoI pixels, on the common coordinate system, of the RoIs of the subjects within the visible spectrum image, and (b) reference object pixels, on the common coordinate system, of the reference object within the visible spectrum image; determining, by the processing circuitry, (a) RoI temperatures of the RoIs of the subjects, by analyzing the identified RoI pixels on the thermal image, (b) a reference temperature by analyzing the reference object pixels on the thermal image and (c) a parameter correlated to an emissivity of the reference object, based on the reference temperature and on the indication of the scene ambient temperature; and upon existence of a difference between the reference temperature and the indication of the scene ambient temperature, correcting, by the processing circuitry, the RoI temperatures, based on the difference and utilizing the parameter, to compensate for the difference, giving rise to corrected RoI temperatures.

In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the presently disclosed subject matter. However, it will be understood by those skilled in the art that the presently disclosed subject matter may be practiced without these specific details. In other instances, well-known methods, procedures, and components have not been described in detail so as not to obscure the presently disclosed subject matter.

Unless specifically stated otherwise, as apparent from the following discussions, it is appreciated that throughout the specification discussions utilizing terms such as "obtaining", "registering", "identifying", "determining", "correcting", "tracking" or the like, include action and/or processes of a computer that manipulate and/or transform data into other data, said data represented as physical quantities, e.g. such as electronic quantities, and/or said data representing the physical objects. The terms "computer", "processor", "processing resource" and "controller" should be expansively construed to cover any kind of electronic device with data processing capabilities, including, by way of non-limiting example, a personal desktop/laptop computer, a server, a computing system, a communication device, a smartphone, a tablet computer, a smart television, a processor (e.g. digital signal processor (DSP), a microcontroller, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), etc.), a group of multiple physical machines sharing performance of various tasks, virtual servers co-residing on a single physical machine, any other electronic computing device, and/or any combination thereof.

The operations in accordance with the teachings herein may be performed by a computer specially constructed for the desired purposes or by a general-purpose computer specially configured for the desired purpose by a computer program stored in a non-transitory computer readable storage medium. The term "non-transitory" is used herein to exclude transitory, propagating signals, but to otherwise include any volatile or non-volatile computer memory technology suitable to the application.

As used herein, the phrase "for example," "such as", "for instance" and variants thereof describe non-limiting embodiments of the presently disclosed subject matter. Reference in the specification to "one case", "some cases", "other cases" or variants thereof means that a particular feature, structure or characteristic described in connection with the embodiment(s) is included in at least one embodiment of the presently disclosed subject matter. Thus, the appearance of the phrase "one case", "some cases", "other cases" or variants thereof does not necessarily refer to the same embodiment(s).

It is appreciated that, unless specifically stated otherwise, certain features of the presently disclosed subject matter, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the presently disclosed subject matter, which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable sub-combination.

In embodiments of the presently disclosed subject matter, fewer, more and/or different stages than those shown in <FIG> may be executed. In embodiments of the presently disclosed subject matter one or more stages illustrated in <FIG> may be executed in a different order and/or one or more groups of stages may be executed simultaneously. <FIG> illustrate a general schematic of the system architecture in accordance with an embodiment of the presently disclosed subject matter. Each module in <FIG> can be made up of any combination of software, hardware and/or firmware that performs the functions as defined and explained herein. The modules in <FIG> may be centralized in one location or dispersed over more than one location. In other embodiments of the presently disclosed subject matter, the system may comprise fewer, more, and/or different modules than those shown in <FIG>.

Bearing this in mind, attention is drawn to <FIG>, a schematic illustration of an example scene with subjects and a reference object, in accordance with the presently disclosed subject matter.

Scene <NUM> includes subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c). The subjects can be human beings, animals, plants, machines or any other heat emitting objects. Scene <NUM> is viewable by one or more sensors. The sensors can take at least one image of scene <NUM> which includes at least part of the subjects and at least part of a reference objects <NUM>. In some cases, at least parts of the subjects are Regions of Interest (RoIs) (e.g. RoI A <NUM>-a, RoI B <NUM>-b, RoI C <NUM>-c). The RoIs can include a face of a respective subject, a forehead of the respective subject, a mouth of the respective subject or any other body part of the respective subject. A non-limiting example can be that subject A <NUM>-a is a human being and RoI A <NUM>-a includes at least an area of subject's A <NUM>-a forehead.

Scene <NUM> can additionally include one or more reference objects <NUM>. Reference object <NUM> can be made of material whose temperature changes in a known manner according to changes to the scene ambient temperature within scene <NUM>. According to the claimed invention, the temperature of the reference object <NUM> is the scene ambient temperature. In some cases, the reference object <NUM> is at least part of a cardboard.

In some cases, the reference object <NUM> is diffusive and not specular, thus does not have mirror-like properties of wave reflection. It is to be noted that reference object <NUM> is not a black body.

In some cases, the reference object <NUM> includes one or more known symbols that are visible to a visible spectrum camera or to a thermal image sensor or to both the visible spectrum camera and the thermal image sensor, in some cases the known symbols are visible to the visible spectrum camera and not to the thermal image sensor, as further detailed herein, inter alia with reference to <FIG>.

Scene <NUM> can be indoors, for example: a reception area of a medical practitioner, where patients await reception by the medical practitioner. In some cases, scene <NUM> is outdoors, for example: scene <NUM> can be part of a park where people and animals are roaming around. In some cases, scene <NUM> is a large space including a large number of subjects, for example: part of a busy airport or train station.

It is to be noted that the subjects within scene <NUM> can be stationary and/or moving within scene <NUM>.

Having briefly described a scene with subjects and a reference object, attention is drawn to <FIG>, a block diagram schematically illustrating one example of a system for measuring temperature of subjects within a scene, in accordance with the presently disclosed subject matter.

According to certain examples of the presently disclosed subject matter, system <NUM> comprises a visible spectrum camera <NUM>. Visible spectrum camera <NUM> is capable of acquiring images of scene <NUM>. Visible spectrum camera <NUM> can be made of one or more sensors capable of acquiring images in at least the visible spectrum. The one or more sensors can be spatially distributed to acquire images of scene <NUM> from one or more locations and/or from one or more viewpoints. In some cases, visible spectrum camera <NUM> is a high-definition camera, having a spatial resolution higher than <NUM>/pixel in the relevant object plane.

In addition, system <NUM> comprises a thermal image sensor <NUM>. The thermal image sensor <NUM> is also capable of acquiring images of scene <NUM>. In some cases, the thermal image sensor <NUM> is an infrared (IR) image sensor capable of acquiring images of scene <NUM> in at least the IR spectrum. In some cases, the thermal image sensor <NUM> is a near-infrared (NIR) image sensor capable of acquiring images of scene <NUM> in at least the NIR spectrum. Thermal image sensor <NUM> can be made of one or more sensors capable of acquiring images in at least the IR. The one or more thermal sensors can be spatially distributed to acquire thermal images of scene <NUM> from one or more locations and/or from one or more viewpoints. In some cases, the thermal image sensor <NUM> is an uncooled thermal image sensor.

System <NUM> can optionally comprise a three-dimensional (3D) camera <NUM>. The 3D camera <NUM> is capable of acquiring 3D images of scene <NUM>. In some cases, 3D camera <NUM> creates digital 3D representations of the subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) and/or the objects located within the scene <NUM>. In some cases, 3D camera <NUM> is a range camera capable of producing an image showing the distance to one or more points in scene <NUM> from a given location. In some cases, 3D camera <NUM> produces a point cloud of scene <NUM>. 3D camera <NUM> can be made of one or more sensors capable of acquiring images of scene <NUM>. The one or more sensors can be spatially distributed to acquire images of scene <NUM> from one or more locations and/or from one or more viewpoints. The 3D camera's <NUM> sensors can be one or more of: a Light Imaging, Detection, and Ranging (LiDAR) sensor, a stereoscopic sensor, a Time of Flight (ToF) sensor, or any combinations thereof.

System <NUM> can further comprise a network interface <NUM> enabling connecting the system <NUM> to a network and enabling it to send and receive data sent thereto through the network, including in some cases receiving information collected from one or more remote sensors, for example: receiving indication of the scene ambient temperature of scene <NUM> from a thermometer that is a location within scene <NUM>. In some cases, the network interface <NUM> can be connected to a Local Area Network (LAN), to a Wide Area Network (WAN), or to the Internet. In some cases, the network interface <NUM> can connect to a wireless network.

System <NUM> can further comprise or be otherwise associated with a data repository <NUM> (e.g. a database, a storage system, a memory including Read Only Memory - ROM, Random Access Memory - RAM, or any other type of memory, etc.) configured to store data, including, inter alia, information defining the spatial location of the RoIs (e.g. RoI A <NUM>-a, RoI B <NUM>-b, RoI C <NUM>-c) within scene <NUM>, point clouds of subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) and/or objects located within scene <NUM>, scene ambient temperature, threshold temperatures, etc. In some cases, data repository <NUM> can be further configured to enable retrieval and/or update and/or deletion of the data stored thereon. It is to be noted that in some cases, data repository <NUM> can be distributed. It is to be noted that in some cases, data repository <NUM> can be stored in on cloud-based storage.

System <NUM> further comprises processing circuitry <NUM>. Processing circuitry <NUM> can be one or more processing circuitry units (e.g. central processing units), microprocessors, microcontrollers (e.g. microcontroller units (MCUs)) or any other computing devices or modules, including multiple and/or parallel and/or distributed processing circuitry units, which are adapted to independently or cooperatively process data for controlling relevant system <NUM> resources and for enabling operations related to system <NUM> resources.

The processing circuitry <NUM> comprises one or more of the following modules: temperature measurement management module <NUM>, respiratory rate determination management module <NUM>, and pulse determination management module <NUM>.

Temperature measurement management module <NUM> can be configured to perform a temperature measurement process, as further detailed herein, inter alia with reference to <FIG>.

Respiratory rate determination management module <NUM> can be configured to perform a respiratory rate determination process, as further detailed herein, inter alia with reference to <FIG>.

Pulse determination management module <NUM> can be configured to perform a pulse determination process, as further detailed herein, inter alia with reference to <FIG>.

Turning to <FIG>, there is shown a flowchart illustrating one example of a sequence of operations carried out for temperature measurement, in accordance with the presently disclosed subject matter.

According to certain examples of the presently disclosed subject matter, system <NUM> can be configured to perform a temperature measurement process <NUM>, e.g. utilizing the temperature measurement management module <NUM>.

For this purpose, system <NUM> is configured to obtain (a) a visible spectrum image captured by the visible spectrum camera <NUM>, and (b) a thermal image captured by the thermal image sensor <NUM>, and (c) an indication of a scene ambient temperature within the scene <NUM> (block <NUM>).

System <NUM> obtains a visible spectrum image of scene <NUM>, which includes subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c), and a reference object <NUM> having an ambient temperature. The visible spectrum image comprises at least part of an RoI (e.g. RoI A <NUM>-a, RoI B <NUM>-b, RoI C <NUM>-c) of at least one of the subjects (e.g. one of: subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c), and the reference object <NUM>. The visible spectrum image is captured by the visible spectrum camera <NUM>.

System <NUM> is configured to obtain a thermal image captured by the thermal image sensor <NUM>. The thermal image comprises the at least RoI (e.g. RoI A <NUM>-a, RoI B <NUM>-b, RoI C <NUM>-c) of each of the subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) as comprised within the visible spectrum image. The thermal image also comprises the reference object <NUM>.

System <NUM> is configured to also obtain an indication of a scene ambient temperature within scene <NUM>. In some cases, the indication of the scene ambient temperature can be obtained from a thermometer measuring ambient temperature within scene <NUM>. The thermometer can be external to system <NUM> or comprised as part of system <NUM>. In some cases, the indication of the scene ambient temperature can be received by system <NUM> from an external source, via a wired or wireless network by utilizing network interface <NUM>. In some case, the indication of the scene ambient temperature can be determined by system <NUM> based on pre-defined properties of scene <NUM>.

In a non-limiting example, system <NUM> obtains a visible spectrum image of scene <NUM> wherein RoI A <NUM>-a of subject A <NUM>-a and the reference object <NUM> are visible. System <NUM> also obtains a thermal image that comprises the thermal readings from RoI A <NUM>-a and the thermal readings from reference object <NUM>. System <NUM> also obtains an indication that the scene ambient temperature within scene <NUM> is <NUM> degrees Celsius.

After obtaining the visible spectrum image, the thermal image, system <NUM> is further configured to register the visible spectrum image and the thermal image onto a common coordinate system (block <NUM>). The registration of the visible spectrum image and the thermal image onto a common coordinate system enables system <NUM> to associate each pixel of the visible spectrum image to the corresponding pixel on the thermal image by utilizing the common coordinate system. In some cases, the registration of the visible spectrum image and the thermal image onto a common coordinate system is required because of parallax effect between the thermal image sensor <NUM> and the visible spectrum camera <NUM>. The registration sustains variation of distance between the sensors (e.g. visible spectrum camera <NUM> and thermal image sensor <NUM>) and subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c and/or the reference object <NUM>).

In some cases, system <NUM> includes a 3D camera <NUM> capable of acquiring depth images of the scene <NUM> comprising the at least RoI (e.g. RoI A <NUM>-a, RoI B <NUM>-b, RoI C <NUM>-c) of each of the subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) as comprised within the visible spectrum image. The registration of the visible spectrum image and the thermal image onto a common coordinate system can include also utilizing the depth images of the scene <NUM> for the registration. In these cases, 3D camera <NUM> can obtain a depth image and system <NUM> can utilize the depth image for the registration of the visible spectrum image and the thermal image onto the common coordinate system in order to sustain variation of distance between the visible spectrum camera <NUM>, the thermal image sensor <NUM>, the 3D camera <NUM> and subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) and/or the reference object <NUM> and/or the reference object <NUM>. The distance dependent registration is required as different parts of scene <NUM> appear at different distance from visible spectrum camera <NUM>, thermal image sensor <NUM> and from 3D camera <NUM>. In some cases, a registration of the visible spectrum image, the thermal image and the depth image is required. In some cases, the registration can be a non-rigid registration. The registration utilizes the knowledge of the distance to each point in scene <NUM>. In some cases, usage of 3D camera <NUM> enables system <NUM> to create a point cloud, in which each point in scene <NUM> is associated with coordinates (e.g. X, Y, Z coordinates) with respect to the location of the 3D camera <NUM>. in some cases, the transformation of coordinates between different sensors (e.g. visible spectrum camera <NUM>, thermal image sensor <NUM> and 3D camera <NUM>) can be evaluated by a preliminary calibration procedure. The preliminary calibration procedure can be realized by utilizing one or more known calibration methods. One non-limiting example is capturing of a given geometric pattern (e.g. a black and white checkboard pattern) observed by all sensors (e.g. visible spectrum camera <NUM>, thermal image sensor <NUM> and 3D camera <NUM>) during substitution of the given geometric pattern in a number of orientations and distances with respect to the sensors (e.g. visible spectrum camera <NUM>, thermal image sensor <NUM> and 3D camera <NUM>) which can be rigidly mounted. Another exemplary method of a preliminary calibration process of the sensors (e.g. visible spectrum camera <NUM>, thermal image sensor <NUM> and 3D camera <NUM>) can be done by capturing an image of an object within scene <NUM> at one or more distances. This exemplary procedure allows an equivalence between the distance and the correct transformation of a point object from one of the sensor (e.g. one of: visible spectrum camera <NUM>, thermal image sensor <NUM> and 3D camera <NUM>) to another sensor (e.g. one of: visible spectrum camera <NUM>, thermal image sensor <NUM> and 3D camera <NUM>). The preliminary calibration methods enable system <NUM> to apply a correction of image aberrations. In some cases, the objects used for the preliminary calibration process are made from materials or are colored in a way that makes them observable by the sensors (e.g. visible spectrum camera <NUM>, thermal image sensor <NUM> and 3D camera <NUM>).

Continuing the above non-limiting example, system <NUM> registers the visible spectrum image and the thermal image onto a common coordination system. The registration allows a pixel-to-pixel correspondence between the pixels of the visible spectrum image and the pixels of the thermal image. In some cases, system <NUM> utilizes a depth image of scene <NUM> for the registration and the depth data may be registered with the visible and the thermal images.

After registering the visible spectrum image and the thermal image onto a common coordinate system, system <NUM> is further configured to identify (a) RoI pixels, on the common coordinate system, of the RoIs (e.g. RoI A <NUM>-a, RoI B <NUM>-b, RoI C <NUM>-c) of the subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) within the visible spectrum image, and (b) reference object pixels, on the common coordinate system, of the reference object <NUM> within the visible spectrum image (block <NUM>).

System <NUM> can identify RoI pixels, on the common coordinate system, of the RoIs (e.g. RoI A <NUM>-a, RoI B <NUM>-b, RoI C <NUM>-c) of the subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) within the visible spectrum image.

System <NUM> can be further configured to identify reference object pixels, on the common coordinate system, of the reference object <NUM> within the visible spectrum image.

The identification of the RoI pixels can be realized by system <NUM> by performing an analysis of the visible spectrum image. The RoI pixels can be for example pixels of the subject's (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) head or of the area of the forehead or nostrils. The reference object pixels are the pixels of the visible spectrum image containing at least part of the reference object <NUM>.

In some cases, the identification of the reference object pixels is based on a known shape of the reference object <NUM>. For example, the reference object <NUM> can have a specific rectangular shape and system <NUM> can analyze the visible spectrum image to identify the specific rectangular shape.

In some cases, the identification of the reference object pixels is based on a known location of the reference object <NUM> within scene <NUM>. For example, the reference object <NUM> can be locates in a lower right corner of scene <NUM> with respect to visible spectrum camera <NUM> and system <NUM> can analyze the visible spectrum image to identify the specific rectangular shape in that location.

In some cases, the reference object <NUM> includes one or more known symbols that are visible to the visible spectrum camera and/or to the thermal image sensor. In some cases, reference object <NUM>, is not visible to the thermal image sensor. In these cases, the identification of the reference object pixels can be realized by system <NUM> analyzing the visible spectrum image to identify at least one of the known symbols.

Continuing the above non-limiting example, RoI A <NUM>-a is the forehead of subject A <NUM>-a. System <NUM> identifies the RoI pixels, which in our example are the pixels of RoI A <NUM>-a by utilizing a head determination algorithm on the visible spectrum image. The reference object <NUM> in our non-limiting example is a cardboard with a known symbol printed thereon. The symbol is visible to visible spectrum camera <NUM>. System <NUM> identifies the reference object pixels by analyzing the visible spectrum image to identify the known symbol.

System <NUM> is further configured to determine RoI temperatures by analyzing respective RoIs pixels on the thermal image and a reference temperature by analyzing the reference object pixels on the thermal image (block <NUM>).

The RoI temperatures can be determined by system <NUM> by using the registration of both the visible spectrum image and the thermal image onto a common coordinate system to locate the RoIs pixels, which were identified by system <NUM> on the visible spectrum image, within the thermal image. These RoI pixels within the thermal image represent temperature of these RoIs (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) of the subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) as measured by thermal image sensor <NUM>.

Continuing the non-limiting example from above, system <NUM> can analyze the RoI pixels associated with RoI A <NUM>-a to determine the RoI temperature of the forehead of subject A <NUM>-a is <NUM> degrees Celsius. Thus, subject's A <NUM>-a temperature seems to be normal.

Similarly, the reference temperature can be determined by system <NUM> by using the registration of both the visible spectrum image and the thermal image onto a common coordinate system to locate the reference object pixels, identified on the visible spectrum image by system <NUM>, within the thermal image. These reference object pixels within the thermal image represent the temperature of the reference object <NUM> as registered by thermal image sensor <NUM>.

Continuing the non-limiting example from above, system <NUM> can analyze the reference object pixels associated with the reference object <NUM> to determine the reference temperature to be <NUM> degrees Celsius.

Upon existence of a difference between the reference temperature and the scene ambient temperature, system <NUM> is further configured to correct the RoI temperatures to compensate for the difference, giving rise to corrected RoI temperatures (block <NUM>).

An exemplary mathematical expression of the correction used to correct the RoI temperatures to compensate for the difference can be the following expression: <MAT>.

Where the exemplary mathematical expression is formed by supposing that one of the measurements was taken at time t1 such that the following values are obtained by system <NUM>:.

System <NUM> obtains an additional measurement at time t2, as follows:.

f(Tamb_1), f(Tamb_2) is a function for correction of the thermal image sensor <NUM> offset as a function of scene ambient temperature. This functionality may be embedded in the thermal imaging sensor <NUM> or may be supplied by its manufacturer. In case of f embedded in the reading of the thermal image sensor, the function f≡<NUM>.

α is a calibration parameter describing the effect of the reference object's <NUM> temperature on the signal measured by the thermal image sensor <NUM>.

The temperature at both moments t1 and t2 are at steady states.

Practically, α depends on emissivity of the reference object's <NUM> material. However, in majority of practical cases the emissivity of the reference object <NUM> cannot be measured, for example: because physical access to the reference object <NUM> is limited. In some embodiments α can be calculated during an adaptive calibration procedure of system <NUM>. In this procedure, the ambient temperature values and the reference object's <NUM> temperature as it is measured by the thermal image sensor <NUM> are measured at a plurality of point in time during a given time interval during which the ambient temperature may change. In <FIG> we show schematic records of a non-limiting example of reference object's <NUM> temperature values <NUM>, measured by the thermal image sensor <NUM> at a plurality of point in time during the given time period, and in <FIG> we depict the ambient temperature measurements <NUM>, measured during the same given time period. <FIG> demonstrate the variations of readings that result from the variation of the ambient temperature. Measurements <NUM> and <NUM> have areas with similar shapes (marked <NUM>), having in some cases different scale, for the ambient temperature measurements <NUM> and for the reference temperature <NUM> as measured by the thermal image sensor <NUM>. Measurements <NUM> and <NUM> have areas with differing shapes (marked <NUM>). These readings result from changes of the thermal image sensor and are not correlated with the ambient temperature of scene <NUM>. Analyzing the readings <NUM> and <NUM> from the ambient temperature of scene <NUM> and from reading from the thermal image sensor <NUM> of the same scene <NUM>, enables evaluation of the parameter α. Example analysis methods include utilizing regression, least mean squares or by other numerical approaches on measurements <NUM> and <NUM>. The detection of areas <NUM> and <NUM> can be performed, for example, by deep learning methods or by other analytical approaches.

As a non-limiting example, we present here a way for calculation of the parameter α:
In this evaluation we suppose that the studied object is the reference object <NUM> itself and its temperature is the ambient temperature is expressed by the following equations: <MAT> <MAT> where k is the kth measurement set of both ambient temperature and the thermal image sensor <NUM> reading. These data sets can be used to calculate the parameter α. For example, it can be done as a calculation of a slope of regression in a function where the T'obj_k represents the y-axis value and Tamb_k represents the argument values. In case that f(Tamb_k) is embedded in the reading of the thermal image sensor <NUM>, the function f(Tamb_k)≡<NUM>.

The above exemplary mathematical expression can provide a correction of the offset shift in the thermal image sensor <NUM>. <FIG> shows a non-limiting example of a simultaneous change in the temperature measuring by the thermal image sensor <NUM> on a human's forehead and on reference object <NUM>. The results shown in <FIG> are the results of <FIG>, after subtraction of graph averages, thus allowing for better
understanding of the correlation between the shift in the human's forehead temperature and the shift reference object <NUM> temperature. The offset shift in the reference temperature measuring can be used for the correction of the body temperature measuring. In some cases, the correction expression can take into account effects of emissivity.

The scene ambient temperature can be obtained by system <NUM> at any phase of process <NUM>. Scene ambient temperature can be measured by a temperature sensor that is part of system <NUM> or by a sensor that is external to system <NUM>.

As explained above, the temperature of reference object <NUM> is expected to be the scene ambient temperature or dependent on the scene ambient temperature on a known regularity. As thermal image sensor <NUM> can be out of calibration, for example: thermal image sensor <NUM> was calibrated in one point in time but has gone out of calibration over time, there may be a difference between the reference temperature - being the temperature of reference object <NUM> as measured by thermal image sensor <NUM>, and the actual temperature of reference object <NUM>, being the scene ambient temperature obtained by system <NUM>. System <NUM> can utilize the RoI temperatures to compensate for the difference, if any, and determine a corrected RoI temperature. System <NUM> can be configured to constantly calibrate thermal image sensor <NUM> utilizing reference object <NUM>. The reference temperature knowledge also assists in reducing overall thermal sensor noise by utilizing noisy shift of the temperature measurement sensed by thermal image sensor <NUM>.

Continuing the non-limiting example from above, system <NUM> obtains an indication that the scene ambient temperature of scene <NUM> is <NUM> degrees Celsius. Therefore, there is a +<NUM> degrees Celsius difference between the reference temperature and the scene ambient temperature. System <NUM> uses the difference to determine the corrected temperature of RoI A <NUM>-a to be <NUM> degrees Celsius. Thus, subject's A <NUM>-a temperature is actually indicative of a body temperature that exceed a threshold of temperture that are considered as healthy.

In some cases, the correction of the RoI temperatures can be also based on a distance of the respective subject (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) from the thermal image sensor <NUM>. In these cases, system <NUM> can use a moisture measuring device to obtain indication of the ambient moisture level and the effect of the moisture on the thermal radiation received by thermal image sensor <NUM> is associated with the distance of the subject (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) from the thermal image sensor <NUM>. In some cases, moisture within scene <NUM> can affect the absorption of the IR radiation and thereby cause a variation of the temperature measured by the thermal image sensor <NUM> as a function of distance between the thermal image sensor <NUM> and the subject (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c). Thus, the correction of the RoI temperatures is dependent on the distance between the thermal image sensor <NUM> and the subject (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c). This correction can provide high accuracy temperature measurements.

Optionally, system <NUM> can further configured to alert an operator of the system upon identifying subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) associated with corrected RoI temperatures exceeding a threshold (block <NUM>).

Continuing the above non-limiting example, an operator of system <NUM> can be looking on a screen of system <NUM> displaying the visible spectrum image and an indication that subject's A <NUM>-a temperature exceeds <NUM> degrees Celsius.

It is to be noted that, with reference to <FIG>, some of the blocks can be integrated into a consolidated block or can be broken down to a few blocks and/or other blocks may be added. Furthermore, in some cases, the blocks can be performed in a different order than described. It is to be further noted that some of the blocks are optional. It should be also noted that whilst the flow diagram is described also with reference to the system elements that realizes them, this is by no means binding, and the blocks can be performed by elements other than those described herein.

<FIG>, is a flowchart illustrating one example of a sequence of operations carried out for respiratory rate determination, in accordance with the presently disclosed subject matter.

According to certain examples of the presently disclosed subject matter, system <NUM> can be further configured to perform a respiratory rate determination process <NUM>, e.g. utilizing the respiratory rate determination management module <NUM>.

For this purpose, system <NUM> can be configured to obtain a sequence of subsequent visible spectrum images captured by the visible spectrum camera <NUM> subsequently to the visible spectrum image and a sequence of subsequent thermal images captured by the thermal image sensor <NUM> subsequently to the thermal image (block <NUM>). A non-limiting example can be a first sequence of visible spectrum images wherein RoI B <NUM>-b is the area of the nostrils of subject B <NUM>-b and is visible in the first sequence and a second sequence of thermal images wherein RoI B <NUM>-b is visible.

After obtaining the first sequence and the second sequence, system <NUM> can be further configured to register the subsequent visible spectrum images and the subsequent thermal images onto the common coordinate system (block <NUM>). The registration allows a pixel-to-pixel translation between the pixels of the first sequence of visible spectrum images and pixels of corresponding thermal images of the second sequence.

After registering the images onto the common coordinate system, system <NUM> can be further configured to identify subsequent RoI pixels, on the common coordinate system, of the RoIs (e.g. RoI A <NUM>-a, RoI B <NUM>-b, RoI C <NUM>-c) of the subjects (e.g. subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) within the subsequent visible spectrum images (block <NUM>). In our non-limiting example, the RoI pixels are the pixels of RoI B <NUM>-b which are pixels in the area of the nostrils of subject B <NUM>-b who is a human being.

After identifying the RoI pixels, system <NUM> can be further configured to track the subsequent RoI pixels within the subsequent thermal images of the thermal images sequence. System <NUM> can track the subsequent RoI pixels within the subsequent thermal images of the thermal images sequence by utilizing the respective subsequent visible spectrum images of the visible spectrum images sequence (block <NUM>). System <NUM> utilizes the subsequent visible spectrum images of the first sequence for the tracking by using known tracking algorithms. The tracking is done by determining the location of the pixels of the RoIs (e.g. RoI A <NUM>-a, RoI B <NUM>-b, RoI C <NUM>-c) in the subsequent visible spectrum images of the visible spectrum images sequence. The system determines the location of the RoIs within each image of the pairs of images of this sequence and thus is able to track the RoI along the sequence of images. In some cases, system <NUM> tracks the subsequent RoI pixels within the subsequent thermal images of the second sequence without usage of the first sequence.

System <NUM> can be further configured to determine a respiratory rate, which is the number of breaths a subject (e.g. one of: subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) takes per minute, of the respective subject (e.g. one of: subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) by analyzing the tracked subsequent RoI pixels for changes in temperature that occur as the respective subject (e.g. one of: subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) exhales air (block <NUM>). System <NUM> can also determine additional temporal information associated with the respiratory rate, such as: inhale time, exhale time, inhale to exhale time ration, etc..

Continuing the non-limiting example above, system <NUM> can determine the respiratory rate of subject B <NUM>-b to be <NUM> breaths per minute, which is within the normal respiration rate range for an adult human being. <FIG> is a non-limiting example of a graph representing respiratory rate of a given subject (e.g. one of: subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) as measured by system <NUM> over a given period of time.

Turning to <FIG>, there is shown a flowchart illustrating one example of a sequence of operations carried out for pulse determination, in accordance with the presently disclosed subject matter.

According to certain examples of the presently disclosed subject matter, system <NUM> can be further configured to perform a pulse determination process <NUM>, e.g. utilizing the pulse determination management module <NUM>.

For this purpose, system <NUM> can be configured to obtain a sequence of subsequent visible spectrum images captured by the visible spectrum camera subsequently to the visible spectrum image (block <NUM>).

A non-limiting example can be a sequence of visible spectrum images wherein RoI C <NUM>-c is the area of the forehead of subject C <NUM>-c who is an adult human being and is visible therein.

After obtaining the sequence, system <NUM> can be further configured to track the RoI (e.g. RoI A <NUM>-a, RoI B <NUM>-b, RoI C <NUM>-c) within the subsequent visible spectrum images of the sequence (block <NUM>). System <NUM> utilizes the subsequent visible spectrum images of the third sequence for the tracking by using known tracking algorithms.

After tracking the RoI (e.g. RoI A <NUM>-a, RoI B <NUM>-b, RoI C <NUM>-c), system <NUM> can be further configured to determine a pulse of the respective subject (e.g. one of: subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) by analyzing changes of color within the RoI (e.g. one of: RoI A <NUM>-a, RoI B <NUM>-b, RoI C <NUM>-c). The changes of color are due to the blood flowing through the veins in accordance with the cardiac cycle of the respective subject (e.g. one of: subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) (block <NUM>).

Continuing the non-limiting example above, system <NUM> can determine the pulse rate of subject C <NUM>-c to be <NUM> beats per minute, which is within the normal resting heart rate range for an adult human being, based on the changes of color of RoI C <NUM>-c within the third sequence. <FIG> is a non-limiting example of a graph representing pulse rate of a subject (e.g. one of: subject A <NUM>-a, subject B <NUM>-b, subject C <NUM>-c) as measured by the system <NUM> over a given period of time.

It is to be understood that the presently disclosed subject matter is not limited in its application to the details set forth in the description contained herein or illustrated in the drawings. The presently disclosed subject matter is capable of other embodiments and of being practiced and carried out in various ways. Hence, it is to be understood that the phraseology and terminology employed herein are for the purpose of description and should not be regarded as limiting. As such, those skilled in the art will appreciate that the conception upon which this disclosure is based may readily be utilized as a basis for designing other structures, methods, and systems for carrying out the several purposes of the present presently disclosed subject matter.

Claim 1:
A system (<NUM>) for measuring temperature of at least two subjects (<NUM>-a, <NUM>-b, <NUM>-c) within a scene (<NUM>) including a reference object (<NUM>), the reference object having an unknown emissivity and an ambient temperature, wherein the ambient temperature of the reference object is the scene ambient temperature, the system comprising:
a visible spectrum camera (<NUM>) configured to acquire images of the scene comprising (a) at least a Region of Interest, RoI (<NUM>-a, <NUM>-b, <NUM>-c), of each of the subjects, and (b) the reference object;
a thermal image sensor (<NUM>) configured to acquire images of the scene comprising (a) at least the RoI of each of the subjects, and (b) the reference object; and
a processing circuitry (<NUM>) configured to:
obtain (a) a visible spectrum image captured by the visible spectrum camera, and (b) a thermal image captured by the thermal image sensor, and (c) an indication of the scene ambient temperature within the scene;
register the visible spectrum image and the thermal image onto a common coordinate system;
identify (a) RoI pixels, on the common coordinate system, of the RoIs of the subjects within the visible spectrum image, and (b) reference object pixels, on the common coordinate system, of the reference object within the visible spectrum image;
determine (a) RoI temperatures of the RoIs of the subjects, by analyzing the identified RoI pixels on the thermal image, (b) a reference temperature by analyzing the reference object pixels on the thermal image, and (c) a parameter correlated to an emissivity of the reference object, based on the reference temperature and on the indication of the scene ambient temperature; and
upon existence of a difference between the reference temperature and the indication of the scene ambient temperature, correct the RoI temperatures, based on the difference and utilizing the parameter, to compensate for the difference, giving rise to corrected RoI temperatures.