Passenger transit validation, gating system and method

Abstract

To provide a method for passenger transit validation and gating for passenger transit from a non-restricted area to a restricted area at a plurality of barrierless gates, a system and a program product.SOLUTION: A method comprises the steps of: identifying a passenger at a passenger identification touchpoint and generating passenger identification data including a passenger face recognition model; recognizing the passenger in a passenger tracking subsystem using 3D image data captured by a 3D camera and the passenger face recognition model, and generating a shape recognition model for the passenger; and tracking the passenger along a path through a plurality of tracking zones with the 3D camera using the shape recognition model. In the transit validation for the passenger, by analyzing the passenger shape recognition model, the passenger's path through the tracking zones is corrected. In response to the transit validation, passenger feedback and supervision signals are generated which indicate whether transit at the barrierless gate is allowed or denied.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to passenger passage verification and gating for passenger passage from an unrestricted area to a restricted area at multiple barrier-less gates, and in particular to methods, systems, and computer program products therefor. [Background technology]

[0002] Passenger processing gates for use in airports are commonly known. Current passage control solutions in the form of movable barrier gates are expensive and perceived as intrusive to passengers. Furthermore, conventional gates are very expensive and complex due to the number of mechanical parts they contain and the safety mechanisms they require to avoid congestion or accidents. Meanwhile, airport authorities desire the complete passenger control security that conventional gates offer, but dislike the high investment cost and intrusive design. Summary of the Invention

[0003] The present disclosure relates to a passenger passage verification and gating method, system, and computer program product for passenger passage from an unrestricted area to a restricted area at a plurality of barrier-less gates as defined by the independent claims. Embodiments are as defined in the dependent claims.

[0004] The disclosed solution is a passage control "gate" that performs the function of a conventional gate but is "barrierless," i.e., it contains no moving parts to prevent unauthorized entry and essentially operates based on pure audio and visual feedback. This means that there is no traditional gated control of passenger flow through an opening and closing physical barrier. The disclosed barrier-less gate uses 3D sensor technology and tracking for passenger passage verification and gating at multiple barrier-less gates, but is configured to detect (essentially) all required intrusion cases, such as fraud or "tailgating," and confirms passage with the same level of security as a conventional gate. The disclosed solution also reduces ongoing operational costs by reducing the number of attendants required to operate multiple lanes of passenger identification.

[0005] According to a first aspect of the present disclosure, a passenger passage verification and gating method for passenger passage from an unrestricted area to a restricted area at a plurality of barrier-less gates includes identifying a passenger at an identification touchpoint based on personal passenger data available at the passenger identification touchpoint, generating a passenger facial recognition model for the identified passenger based on visual data derived from a face capture sensor at the passenger identification touchpoint, and generating passenger identification data including a tracking ID and the passenger facial recognition model assigned to the identified passenger. The method further includes passing the passenger identification data including the tracking ID and the passenger facial recognition model from the passenger identification touchpoint to a passenger tracking subsystem. The method further includes, in a passenger tracking subsystem, capturing 3D image data of a passenger in a tracking zone using at least one overhead 3D camera and recognizing a passenger having an assigned tracking ID using the captured 3D image data and a passenger facial recognition model, the tracking zone being one of a plurality of tracking zones defining a passageway through a barrier-less gate; generating a shape recognition model for the passenger having the assigned tracking ID, the passenger shape recognition model being derived from the 3D image data captured by the 3D camera; and tracking the passenger along a path through the tracking zone by capturing successive images of the passenger's shape with the 3D camera. The method further includes verifying passage for the passenger by analyzing the passenger's shape captured by the 3D camera in the tracking zone against the passenger shape recognition model, the successive images being captured at successive positions in the passenger's path through the tracking zone. The method further includes correcting the passenger shape recognition model for changes in the passenger's distance and relative position with respect to the 3D camera and for a perspective transformation in response to the passenger's distance and position with respect to the 3D camera for successive images being captured in the passenger's path through the tracking zone.The method further includes the steps of generating a passenger feedback signal in response to the result of the passage confirmation, the passenger indicating whether passage at the barrier-less gate is permitted or denied, and generating a monitoring signal indicative of the result of the passage confirmation to an observer, wherein the monitoring signal is generated and indicated to the observer for each of the plurality of barrier-less gates.

[0006] According to one embodiment, the passage verification for the passenger takes into account the size, height, shape and position of the passenger as captured by the 3D camera, and verifies the continuity, variations and anomalies of the passenger's shape as captured by the 3D camera, and the continuity, variations and anomalies of the comparison of the passenger's shape as captured by the 3D camera, and the continuity, variations and anomalies of the continuously updated passenger shape recognition model as the passenger is tracked along a path through the tracking zone.

[0007] According to another embodiment, the passage verification for the passenger takes into account the speed of the passenger captured by the 3D camera and verifies the continuity, variations and anomalies of the passenger's shape captured by the 3D camera as the passenger is tracked along a path through the tracking zone, and the continuity, variations and anomalies of the comparison of the passenger's shape captured by the 3D camera and the continuity, variations and anomalies of the continuously updated passenger shape recognition model.

[0008] According to a further embodiment, the step of identifying the passenger at the identification touchpoint includes generating location data indicative of the passenger's location at the identification touchpoint, wherein the location data is utilized in recognizing the passenger having the tracking ID assigned by the 3D camera after handover of the passenger identification data, including the tracking ID, the location data, and the passenger facial recognition model, from the passenger identification touchpoint to the passenger tracking subsystem.

[0009] According to one embodiment, the number of tracking zones within a plurality of tracking zones defining a passage through a barrier-less gate is dynamically configurable.

[0010] According to one embodiment, the shape recognition model includes only the passenger's upper torso information, and the passage confirmation for the passenger is performed by analyzing the passenger's torso shape captured by the 3D camera in the tracking zone against the passenger's torso shape recognition model.

[0011] In a modification of the latter embodiment, information from the legs and related movements is captured by additional position sensors and analyzed for passage confirmation in combination with analyzing the passenger's torso shape captured by the 3D camera in the tracking zone against a passenger torso shape recognition model.

[0012] According to one embodiment, to analyze the passenger shape captured by the 3D camera against the passenger shape recognition model, two-dimensional representations are generated from both the passenger shape captured by the 3D camera and the passenger shape recognition model and are iteratively compared in a calibration process.

[0013] According to a second aspect of the present disclosure, a passenger passage verification and gating system for passenger passage from an unrestricted area to a restricted area at a plurality of barrier-less gates is provided, configured to perform a method as described herein.

[0014] Furthermore, according to a third aspect of the present disclosure, there is provided a computer program product for passenger passage verification and gating for passenger passage from an unrestricted area to a restricted area at a plurality of barrier-less gates, the program, when executed by a computer, causing the computer to perform the method described herein.

[0015] The computer program contains instructions that, when executed by a computer, cause the computer to perform the methods and processes as described herein with reference to various aspects of the present disclosure.

[0016] Embodiments and further aspects of the disclosure are defined by the dependent claims.

[0017] The foregoing and further objects, features and advantages of the present subject matter will become apparent from the following description of illustrative embodiments taken in conjunction with the accompanying drawings, in which like or similar numerals are used to represent like elements. [Brief explanation of the drawings]

[0018] [Figure 1] 1 illustrates, in perspective view, one embodiment of a plurality of barrier-less gates capable of implementing passenger passage verification and gating for passenger passage from an unrestricted area to a restricted area in accordance with various aspects of the present disclosure. [Figure 2] 1 illustrates a block diagram of a passenger passage verification and gating system for passenger passage from an unrestricted area to a restricted area at multiple barrier-less gates according to one embodiment of the present disclosure. [Figure 3] FIG. 1 illustrates an embodiment of identifying a passenger at a passenger identification touchpoint based on individual passenger data, generating passenger identification data including a tracking ID and a passenger facial recognition model to be assigned to the identified passenger, and passing the passenger identification data from the passenger identification touchpoint to a passenger tracking subsystem, according to one aspect of the disclosure. [Figure 4] FIG. 1 illustrates an embodiment of identifying a passenger at a passenger identification touchpoint based on individual passenger data, generating passenger identification data including a tracking ID and a passenger facial recognition model to be assigned to the identified passenger, and passing the passenger identification data from the passenger identification touchpoint to a passenger tracking subsystem, according to one aspect of the disclosure. [Figure 5] FIG. 10 illustrates passenger passage confirmation by continuously analyzing the passenger's shape captured by a 3D camera in multiple tracking zones according to one embodiment of the present disclosure. [Figure 6] FIG. 10 illustrates passage confirmation for passengers that takes into account the passenger's velocity as captured by a 3D camera when tracking the passenger along a path through multiple tracking zones, according to another aspect of the present disclosure. [Figure 7]FIG. 10 illustrates passage confirmation for a passenger in which only the upper torso information of the passenger's torso shape captured in 3D is analyzed for passage confirmation according to another embodiment of the present disclosure, and in accordance with yet another embodiment of the present disclosure, information from the legs and related movements is captured by additional position sensors and additionally analyzed. [Figure 8] FIG. 10 illustrates an example of parallel aircraft boarding, where passengers needing assistance are processed separately and the remaining passengers can continue boarding while the exception is processed, according to one or more of various aspects of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0019] FIG. 1 illustrates in perspective view one embodiment of multiple barrier-less gates capable of passenger passage verification and gating for passenger passage from an unrestricted area to a restricted area according to one aspect of the present disclosure.

[0020] As shown in Figure 1, there are multiple gates 110, 120, 130, 140, 150 that provide passenger passage from an unrestricted area to a restricted area, such as for boarding an aircraft at an airport. Gates 110-150 lack mechanical barriers, i.e., are "barrier-less gates." In the illustrated embodiment, each gate 110-150 is equipped with a 3D overhead camera 111, 121, 131, 141, 151. The 3D cameras are adapted to capture 3D image data of passengers and to track the position of any passengers en route through the gate.

[0021] In particular, a 3D camera, such as those indicated in FIG. 1 by reference numerals 111, 121, 131, 141, and 151, is generally an image capture device capable of providing output signals that represent three-dimensional coordinates for each pixel of a captured object, thereby enabling, for example, x, y, and depth coordinates to be determined for each pixel. In FIGS. 3-8, the 3D camera is referred to by "3D" and is generally represented as a stereo camera, as is well known to those skilled in the art. Alternatively, the 3D camera may more generally be any other image capture device capable of providing output signals that represent three-dimensional coordinates for each pixel of a captured object. Also, instead of the exemplary x, y, and depth coordinates mentioned, other spatial 3D coordinates may also be generated for each pixel of a captured object.

[0022] Additionally, in the illustrated embodiment, each gate 110-140 is equipped with a display device 112, 122, 132, 142 (not shown for gate 150) that serves to indicate to passengers in the form of a visual and / or audio passenger feedback signal whether passage at the barrier-less gate is permitted or denied as a result of the passenger passage verification process performed as the passenger is along their path through the gate.

[0023] Additionally, a monitoring signal is generated in response to the result of the passenger passage confirmation, indicating the result of the passage confirmation to a monitor located at the attendant assistance desk 160. A monitoring signal is generated and indicated to a monitor for each of the plurality of barrier-less gates 110-150 so that the monitor can monitor each of the plurality of gates. Thus, the monitor can assist or intervene in any cases of fraudulent activity, "tailgating," or if an unidentified passenger attempts to pass through a gate.

[0024] Before passing through the gate, the passenger is identified at a passenger identification touchpoint, as will be described below with reference to Figures 2, 3 and 4, and the passenger identification data generated at the passenger identification touchpoint is passed to a passenger tracking subsystem for tracking the passenger along their path through the gate and for passage verification for the passenger.

[0025] FIG. 2 shows an overall block diagram of a passenger passage verification and gating system for passenger passage from an unrestricted area to a restricted area at multiple barrier-less gates according to one embodiment of the present disclosure, the system comprising a passenger identification touchpoint 200 and passenger tracking subsystems 300, 400, 500.

[0026] The passenger identification touchpoint 200 includes a passenger location unit 210 and a passenger identification unit 220 that locate and identify passengers. At the passenger identification touchpoint 200, passengers are identified based on personal passenger data (ID-yyyy) available at the identification touchpoint 200, as illustrated in FIG. 3. Based on visual data derived from a face capture sensor associated with the passenger identification unit 220, the passenger identification unit generates a passenger facial recognition model 230. The passenger identification data ID generated at the passenger identification touchpoint 200 includes a tracking ID (FIG. 3) assigned to the identified passenger PAX and the passenger facial recognition model 230 (FIG. 2).

[0027] Once passenger identification data IDs are generated at the passenger identification touchpoint 200, the system provides for the passing of these passenger identification data IDs, including the tracking IDs and passenger facial recognition models, from the passenger identification touchpoint 200 to the passenger tracking subsystems 300, 400, 500.

[0028] As illustrated in Figures 3 and 4, an overhead 3D camera, referenced by "3D," is provided to capture 3D image data of passenger PAX as he or she proceeds from passenger identification touchpoint 200 to tracking zone Z1, which is one of a plurality of tracking zones Z1-Z5 that define a passageway through one of barrier-less gates 110, 120, 130, 140, 150 (Figure 1).

[0029] The passenger tracking subsystem 300, 400, 500 is configured to recognize passengers having assigned tracking IDs based on the passenger facial recognition model 230 delivered from the passenger identification touchpoint 200 along with the 3D image data and passenger identification data ID captured by the overhead 3D cameras 111, 121, 131, 141, 151. Additionally, the passenger tracking subsystem 300 is configured to generate a shape recognition model for the passenger, the passenger shape recognition model being derived from the 3D image data captured by the 3D cameras.

[0030] Furthermore, the tracking subsystems 300, 400, 500 are configured to track passenger PAX along a path through tracking zones Z1-Z5 by continuously capturing images of the passenger's shape with the 3D cameras 111, 121, 131, 141, 151, and to perform passage verification for the passenger by analyzing the passenger's shape captured by the 3D cameras against a passenger shape recognition model. During the passage verification process, the passenger shape recognition model is iteratively modified with respect to changes in the passenger's distance and relative position with respect to the 3D cameras.

[0031] Although the analysis of the passenger shape captured by the 3D camera against the passenger shape recognition model can be done in 3D, the shape changes in the zone can also be calibrated by using a standard camera calibration process based on a standard 2D / 3D camera calibration algorithm to improve the anomaly detection accuracy. That means that to analyze the passenger shape captured by the 3D camera against the passenger shape recognition model, 2D representations are generated from both and compared iteratively in the calibration process. This can significantly reduce the computational power required for the analysis process.

[0032] Finally, the tracking subsystems 300, 400, 500 are configured to generate a passenger feedback signal in response to the passage confirmation result 600 indicating to the passenger whether passage is permitted or denied at the barrier-less gate, and to generate a monitoring signal indicative of the passage confirmation result to an observer at the attendant assistance desk 160 (FIG. 1), the monitoring signal being generated and indicated to the observer for each of the plurality of barrier-less gates.

[0033] Referring back to Figure 2, tracking subsystem 300, 400, 500 includes a block 300, which is shown in the diagram as a "tracking block" and which comprises multiple processing units for passenger tracking. In the embodiment of Figure 2, these processing units include a zone definition unit 310, a shape analysis unit 320, a speed analysis unit 330, a depth analysis unit 340, and a position analysis unit 350. While Figure 2 illustrates all these units, in some embodiments only some but not all of them may be included.

[0034] According to one embodiment, tracking subsystems 300, 400, 500 perform shape analysis on passenger PAX while on a path along tracking zones Z1-Z5, as described herein with reference to FIGS.

[0035] A passenger with an assigned tracking ID is recognized in tracking zone Z1, as illustrated in FIG. 4, based on 3D image data captured by an overhead 3D camera and a passenger face recognition model, and once a shape recognition model is generated for the passenger, a shape analysis process is performed based on data provided by zone definition unit 310, shape analysis unit 320 and position analysis unit 350.

[0036] During this shape analysis process, illustrated schematically in FIG. 5, successive images of the passenger are captured at successive positions in the passenger's path through tracking zones Z1, Z2, Z3, Z4, Z5, the tracking zones being defined by zone definition unit 310, and the position of passenger PAX being determined by position analysis unit 350.

[0037] As the passenger progresses along a path through tracking zones Z1-Z5, the passenger shape recognition model is modified with respect to changes in the passenger's distance and relative position relative to the 3D camera, and the passenger shape recognition model is also modified with respect to perspective transformation depending on the passenger's distance and position relative to the 3D camera for successive images. That is, due to the nature of the camera's field of view and the general behavior of perspective transformation of objects when viewed through an optical system, one and the same object will appear to have a different shape depending on which zone it is located in. Thus, the passenger's shape from the overhead camera undergoes a transformation based on the zone placement. Knowledge of this transformation across different zones effectively aids in tracking the passenger throughout the path and in preventing any kind of fraud, unauthorized entry, or "tailgating."

[0038] In particular, according to one aspect of the present disclosure, the tracking subsystems 300, 400, 500 are configured to check the passage of passenger PAX taking into account the size, height, shape and position of the passenger captured by the 3D cameras 111, 121, 131, 141, 151, and to check the continuity, variations and anomalies of the passenger's shape captured by the 3D cameras, and the continuity, variations and anomalies of the comparison of the passenger's shape captured by the 3D cameras, and the continuity, variations and anomalies of the continuously updated passenger shape recognition model when tracking the passenger along a path through tracking zones Z1, Z2, Z3, Z4, Z5.

[0039] Additionally, according to another aspect, tracking subsystems 300, 400, 500 perform a speed analysis on passenger PAX while on a route along tracking zones Z1-Z5, as described herein with reference to FIG.

[0040] According to this embodiment, the speed analysis process is performed similarly to the shape analysis process by the zone definition unit 310, shape analysis unit 320 and position analysis unit 350, but additionally based on data provided by the speed analysis unit 330.

[0041] Similar to the shape analysis process, successive images of the passenger are captured at successive positions on the passenger's path through tracking zones Z1, Z2, Z3, Z4, Z5, the tracking zones being defined by zone definition unit 310, and the position of passenger PAX being determined by position analysis unit 350. Again, as the passenger progresses along the path through tracking zones Z1-Z5, the passenger shape recognition model is modified with respect to changes in the passenger's distance and relative position with respect to the 3D cameras 111, 121, 131, 141, 151, and with respect to perspective transformations depending on the passenger's distance and position with respect to the 3D cameras for successive images.

[0042] Furthermore, the speed of the passenger captured by the 3D cameras 111, 121, 131, 141, 151 is evaluated by the speed analysis unit 330 and the continuity, variations and anomalies in the shape and speed of the passenger captured by the 3D cameras are compared with a continuously updated passenger shape recognition model as the passenger is tracked along a path through tracking zones Z1-Z5.

[0043] That is, apart from general object tracking, the speed at which passengers move through different zones can be measured, serving as important information for detecting any kind of anomalous behavior. In particular, when an object moves with a constant velocity in the view of an overhead camera, the object will appear to move faster when it is closer to the camera than when it is farther away.

[0044] Considering the overhead cameras 111, 121, 131, 141, 151, passengers appear to move fastest when they are in the intermediate zone, here zone Z3, compared to zones farther away from the cameras, here zones Z2 and Z4 and Z1 and Z5, respectively. This information is modeled for each zone by analyzing the momentum of object movement. Momentum can be calculated by well-known methods, such as MACD (Moving Average Convergence Divergence) or related methods.

[0045] Thus, according to one aspect of the present disclosure, the tracking subsystems 300, 400, 500 are configured to check the passage of passengers by taking into account the speed of the passengers captured by the 3D cameras 111, 121, 131, 141, 151, and to check the continuity, variations and anomalies of the passenger shape and speed captured by the 3D cameras, as well as the continuity, variations and anomalies of the comparison of the passenger shape and speed captured by the 3D cameras, and the continuity, variations and anomalies of the continuously updated passenger shape recognition model when tracking the passenger along a path through tracking zones Z1, Z2, Z3, Z4, Z5.

[0046] In response to the result of the passage verification, as indicated by reference numeral 600 in FIG. 2, the passenger passage verification and gating system generates a passenger feedback signal indicating to passenger PAX whether passage at the barrier-less gate is permitted or denied.

[0047] Furthermore, the passenger passage confirmation and gating system generates a monitoring signal indicating the result of the passage confirmation to the monitor, and the monitoring signal is generated and indicated to the monitor for each of the plurality of barrier-less gates.

[0048] As shown in FIG. 8, which illustrates an example of parallel aircraft boarding with multiple passenger PAXs passing through a barrier-less gate, passenger PAXs requiring assistance (in bold) are handled separately by an assistance agent AGT at agent assistance desk 160. However, other passengers can continue boarding while the exception is being handled. Such "parallel processing," according to one aspect of the present disclosure, contrasts with the serial process of traditional boarding, where, when a passenger requires assistance, they must have their assistance resolved before passengers behind them can proceed.

[0049] The embodiment of Figure 8 illustrates two 3D cameras, each referred to by "3D," one for each of the two illustrated gating lanes. According to another embodiment, instead of one 3D camera for each lane, there could be one 3D camera for two or more gating lanes if the analysis process is powerful enough.

[0050] According to one embodiment of the present disclosure, the system is configured such that identifying passenger PAX at the identification touchpoint 200 includes generating location data indicative of the passenger's location at the identification touchpoint, and the location data is utilized in recognizing the passenger having the tracking ID assigned by the 3D cameras 111, 121, 131, 141, 151 after handover of the passenger identification data ID from the passenger identification touchpoint 200 to the passenger tracking subsystem 300. That means that the location data indicative of the passenger's location at the identification touchpoint 200 "helps find" the passenger after handover from the passenger identification touchpoint 200 to the passenger tracking subsystem 300.

[0051] According to another embodiment of the present disclosure, the tracking subsystem 300, 400, 500 is configured such that the number of tracking zones within a plurality of tracking zones Z1, Z2, Z3, Z4, Z5 that define a passage through a barrier-less gate is dynamically configurable.

[0052] Referring now to FIG. 7, according to yet another aspect of the present disclosure, the tracking subsystems 300, 400, 500 are configured such that the shape recognition model includes only upper torso information of the passenger, and passage confirmation for the passenger is performed by analyzing the passenger's torso shape captured by the 3D camera in tracking zones Z1, Z2, Z3, Z4, Z5 against the passenger's torso shape recognition model.

[0053] According to a modification of the latter embodiment, as also illustrated in Figure 7, the system is configured such that information from the legs and related movements is captured by additional position sensors S1, S2, S3, S4, S5 and analyzed for passage confirmation in combination with analyzing the passenger's torso shape captured by the 3D camera in tracking zones Z1, Z2, Z3, Z4, Z5 against a passenger's torso shape recognition model.

[0054] Additionally, according to another aspect, the present disclosure relates to a passenger passage verification and gating computer program product for passenger passage from an unrestricted area to a restricted area at a plurality of barrier-less gates.

[0055] The computer program contains instructions that, when executed by a computer, cause the computer to perform the methods and processes as described herein with reference to various aspects of the present disclosure. The computer-readable program instructions may be loaded into a computer, another type of programmable data processing apparatus, or may be loaded from another device, from a computer-readable storage medium, or over a network to or from an external computer or external storage device, as is well known to those skilled in the art.

[0056] While particular embodiments and variations have been described herein, it should be recognized that further modifications and alternatives will be apparent to those skilled in the art. In particular, examples are given to illustrate principles and to provide some specific methods and arrangements for putting those principles into practice. [Explanation of symbols]

[0057] 110, 120, 130, 140, 150 gates 111, 121, 131, 141, 151 3D overhead camera 112, 122, 132, 142 display devices 160 Staff Support Desk 200 passenger identification touchpoints 210 Passenger Location Unit 220 Passenger Identification Unit 230 Passenger Face Recognition Model 300, 400, 500 Passenger Tracking Subsystem 310 Zone Definition Unit 320 Shape Analysis Unit 330 Velocity Analysis Unit 340 Depth Analysis Unit 350 Location Analysis Unit 600 results PAX Passenger S1, S2, S3, S4, S5 position sensors Z1, Z2, Z3, Z4, Z5 Tracking Zones

Claims

1. 1. A passenger passage confirmation and gating method for passenger passage from a non-restricted area to a restricted area at a plurality of barrier-less gates, comprising: - identifying a passenger at a passenger identification touchpoint based on personal passenger data available at the identification touchpoint, generating a passenger facial recognition model for the identified passenger based on visual data derived from a face capture sensor at the passenger identification touchpoint, and generating passenger identification data including a tracking ID and the passenger facial recognition model assigned to the identified passenger; - passing the passenger identification data, including the tracking ID and the passenger facial recognition model, from the passenger identification touchpoint to a passenger tracking subsystem; - in the passenger tracking subsystem, capturing 3D image data of the passenger in a tracking zone using at least one overhead 3D camera and recognizing the passenger having the assigned tracking ID using the captured 3D image data and the passenger facial recognition model, the tracking zone being one of a plurality of tracking zones defining a passageway through a barrier-less gate; - generating a shape recognition model for the passenger having the assigned tracking ID, the passenger shape recognition model being derived from 3D image data captured by the 3D camera; - tracking the passenger along a path through the tracking zone by capturing successive images of the passenger's shape with the 3D camera; - performing passage verification for the passenger by analyzing the passenger's shape captured by the 3D camera in the tracking zone against the passenger shape recognition model, wherein successive images are captured at successive positions in the passenger's path through the tracking zone; - the passenger shape recognition model is modified for changes in distance and relative position of the passenger with respect to the 3D camera and for a perspective transformation in response to the distance and position of the passenger with respect to the 3D camera for the successive images being captured on the passenger's path through the tracking zone; - generating a passenger feedback signal in response to a result of the passage confirmation, the passenger being indicated whether passage at the barrier-less gate is permitted or denied, and generating a monitoring signal to an observer indicating the result of the passage confirmation, wherein a monitoring signal is generated and indicated to the observer for each of the plurality of barrier-less gates.

2. 2. The method of claim 1, wherein the passage verification for the passenger takes into account the size, height, shape and position of the passenger captured by the 3D camera, and checks for continuity, variations and anomalies in the passenger's shape captured by the 3D camera and in a comparison of the passenger's shape captured by the 3D camera and in a continuously updated passenger shape recognition model when tracking the passenger along the path through the tracking zone.

3. 3. The method of claim 1 or 2, wherein the passage verification for the passenger takes into account the speed of the passenger captured by the 3D camera and checks for continuity, fluctuations and anomalies in the shape and speed of the passenger captured by the 3D camera and a comparison of the shape and speed of the passenger captured by the 3D camera and the continuously updated passenger shape recognition model when tracking the passenger along a path through the tracking zone.

4. 4. The method of claim 1, wherein the step of identifying the passenger at the identification touchpoint includes generating location data indicating a position of the passenger at the identification touchpoint, and the location data is utilized in recognizing the passenger having the assigned tracking ID by the 3D camera after delivery of the passenger identification data including the tracking ID, the location data, and the passenger facial recognition model from the passenger identification touchpoint to the passenger tracking subsystem.

5. 5. The method of claim 1, wherein the number of tracking zones in the plurality of tracking zones that define the passage through the barrier-less gate is dynamically configurable.

6. 6. The method of claim 1, wherein the shape recognition model includes only upper torso information of the passenger, and passage confirmation for the passenger is performed by analyzing the passenger's torso shape captured by the 3D camera in the tracking zone against the passenger's torso shape recognition model.

7. 7. The method of claim 6, wherein information from legs and related movements is captured by additional position sensors and analyzed for passage confirmation in combination with analyzing the passenger's torso shape captured by the 3D camera in the tracking zone against a passenger's torso shape recognition model.

8. 8. The method of claim 1, wherein two-dimensional representations are generated from the passenger's shape captured by the 3D camera and from the passenger's shape recognition model and are iteratively compared in a calibration process to analyze the passenger's shape captured by the 3D camera against the passenger shape recognition model.

9. 1. A passenger passage verification and gating system for passenger passage from an unrestricted area to a restricted area at a plurality of barrier-less gates, comprising: - identifying a passenger (PAX) at a passenger identification touchpoint (200) based on personal passenger data (ID-yyyy) available at the passenger identification touchpoint (200), generating a passenger facial recognition model for the identified passenger based on visual data derived from a face capture sensor at the passenger identification touchpoint (200), and generating passenger identification data (ID) including a tracking ID and the passenger facial recognition model to be assigned to the identified passenger (PAX); - passing the passenger identification data (ID) including the tracking ID and the passenger facial recognition model from the passenger identification touchpoint (200) to a passenger tracking subsystem (300); - in the passenger tracking subsystem (300), capturing 3D image data of the passenger (PAX) in a tracking zone using at least one overhead 3D camera (111, 121, 131, 141, 151), and recognizing the passenger having the assigned tracking ID using the captured 3D image data and the passenger facial recognition model, the tracking zone (Z1) being one of a plurality of tracking zones (Z1, Z2, Z3, Z4, Z5) defining a passage through a barrier-less gate (110, 120, 130, 140, 150); - generating a shape recognition model for the passenger (PAX) having the assigned tracking ID, wherein the passenger shape recognition model is derived from 3D image data captured by the 3D camera (111, 121, 131, 141, 151); - tracking said passenger (PAX) along a path through said tracking zone by capturing successive images of said passenger's shape with said 3D camera (111, 121, 131, 141, 151); - performing a passage verification (310, 320, 330, 340, 350, 400, 500) for the passenger (PAX) having the assigned tracking ID by analyzing the passenger's shape captured by the 3D cameras (111, 121, 131, 141, 151) in the tracking zones (Z1, Z2, Z3, Z4, Z5) against the passenger shape recognition model, wherein successive images are captured at successive positions in the passenger's path through the tracking zones, and the passenger shape recognition model is corrected for changes in the distance and relative position of the passenger (PAX) with respect to the 3D cameras (111, 121, 131, 141, 151) and for a perspective transformation as a function of the distance and position of the passenger (PAX) with respect to the 3D cameras (111, 121, 131, 141, 151) for the successive images being captured in the passenger's path through the tracking zones, - in response to the result of the passage confirmation (600), generate a passenger feedback signal indicating to the passenger (PAX) whether passage at the barrier-less gate is permitted or denied, and generate a monitoring signal to an observer (AGT) indicating the result of the passage confirmation, the monitoring signal being generated and indicated to the observer for each of the plurality of barrier-less gates.

10. 10. The system of claim 9, wherein the passage verification for the passenger (PAX) takes into account the size, height, shape and position of the passenger captured by the 3D cameras (111, 121, 131, 141, 151) and is configured to verify continuity, variations and anomalies in the shape of the passenger captured by the 3D cameras and in a comparison of the shape of the passenger captured by the 3D cameras and in the continuously updated passenger shape recognition model when tracking the passenger along the path through the tracking zones (Z1, Z2, Z3, Z4, Z5).

11. 11. The system of claim 9 or 10, wherein the passage verification for the passenger is configured to take into account the speed of the passenger captured by the 3D cameras (111, 121, 131, 141, 151) and to verify continuity, variations and anomalies in the shape and speed of the passenger captured by the 3D cameras and in a comparison of the shape and speed of the passenger captured by the 3D cameras and in the continuously updated passenger shape recognition model when tracking the passenger along a path through the tracking zones (Z1, Z2, Z3, Z4, Z5).

12. 12. The system of claim 9, wherein identifying the passenger (PAX) at the identification touchpoint (200) includes generating location data indicating the position of the passenger (PAX) at the identification touchpoint, and wherein the location data is utilized in recognizing the passenger having the assigned tracking ID by the 3D camera (111, 121, 131, 141, 151) after handover of the passenger identification data (ID) including the tracking ID, the location data, and the passenger facial recognition model from the passenger identification touchpoint (200) to the passenger tracking subsystem (300).

13. 13. The system of claim 9, wherein the number of tracking zones within the plurality of tracking zones (Z1, Z2, Z3, Z4, Z5) that define the passage through the barrier-less gate is configured to be dynamically configurable.

14. 14. The system according to claim 9, wherein the shape recognition model includes only upper torso information of the passenger, and wherein passage confirmation for the passenger is performed by analyzing the passenger's torso shape captured by the 3D cameras (111, 121, 131, 141, 151) in the tracking zones (Z1, Z2, Z3, Z4, Z5) against the passenger's torso shape recognition model.

15. 15. The system of claim 14, wherein information from legs and related movements is captured by additional position sensors (S1, S2, S3, S4, S5) and is configured to be analyzed for passage confirmation in combination with analyzing the passenger's torso shape captured by the 3D cameras (111, 121, 131, 141, 151) in the tracking zones (Z1, Z2, Z3, Z4, Z5) against a passenger's torso shape recognition model.

16. 16. The system of claim 9, wherein two-dimensional representations are generated from both the passenger's shape captured by the 3D camera and the passenger's shape recognition model, and the two-dimensional representations are iteratively compared in a calibration process to analyze the passenger's shape captured by the 3D camera against the passenger shape recognition model.

17. A computer program product comprising program code instructions stored on at least one computer readable medium, said program code instructions being adapted to perform the method of any one of claims 1 to 8 when executed on a computer.

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