ESTIMATION OF OBJECT PROPERTIES IN 3D WORLD

• US 20120314030A1
• Filed: 06/07/2011
• Published: 12/13/2012
• Est. Priority Date: 06/07/2011
• Status: Active Grant

• Current Assignee: Kyndryl Incorporated (Kyndryl Holdings, Inc.)
• Original Assignee: International Business Machines Corporation
• Inventors: Datta, Ankur, Feris, Rogerio S., Zhai, Yun
• Granted Patent: US 8,842,163 B2
• Time in Patent Office: Days
• US Class Current: 348/44
• CPC Class Codes: G06T 15/205 Image-based rendering
• CPC Class Codes: G06T 17/10 Constructive solid geometry [CSG] using solid primitives, e.g. cylinders, cubes
• CPC Class Codes: G06T 19/20 Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
• CPC Class Codes: G06T 2200/24 involving graphical user interfaces [GUIs]
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 2207/30236 Traffic on road, railway or crossing
• CPC Class Codes: G06T 2219/2004 Aligning objects, relative positioning of parts
• CPC Class Codes: G06T 2219/2016 Rotation, translation, scaling
• CPC Class Codes: G06T 3/20 Linear translation of whole images or parts thereof, e.g. panning
• CPC Class Codes: G06T 3/40 Scaling of whole images or parts thereof, e.g. expanding or contracting
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06T 7/251 involving models
• CPC Class Codes: G06T 7/62 of area, perimeter, diameter or volume
• CPC Class Codes: G06T 7/75 involving models
• CPC Class Codes: G06V 20/40 in video content extracting overlay text G06V20/62; video retrieval G06F16/70; processing of video elementary streams in video servers H04N21/234; processing of video elementary streams in video clients H04N21/44
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: H04N 13/264 using the relative movement of objects in two video frames or fields
• CPC Class Codes: H04N 13/293 Generating mixed stereoscopic images; Generating mixed monoscopic and stereoscopic images, e.g. a stereoscopic image overlay window on a monoscopic image background
• CPC Class Codes: H04N 2013/0088 Synthesising a monoscopic image signal from stereoscopic images, e.g. synthesising a panoramic or high resolution monoscopic image

Abstract

Objects within two-dimensional (2D) video data are modeled by three-dimensional (3D) models as a function of object type and motion through manually calibrating a 2D image to the three spatial dimensions of a 3D modeling cube. Calibrated 3D locations of an object in motion in the 2D image field of view of a video data input are computed and used to determine a heading direction of the object as a function of the camera calibration and determined movement between the computed 3D locations. The 2D object image is replaced in the video data input with an object-type 3D polygonal model having a projected bounding box that best matches a bounding box of an image blob, the model oriented in the determined heading direction. The bounding box of the replacing model is then scaled to fit the object image blob bounding box, and rendered with extracted image features.

Claims

1. A method for modeling objects within two-dimensional (2D) video data by three-dimensional (3D) models as a function of object type and motion, the method comprising:

calibrating a 2D image field of view of a video data input of a camera to three spatial dimensions of a 3D modeling cube via a user interface of an application executing on a processor, wherein each of the 3D modeling cube three spatial dimensions are at right angles with respect to each other of the three spatial dimensions;

in response to observing an image of an object in motion in the 2D image field of view of a video data input, computing an initial 3D location of the observed 2D object image via the processor as an intersection between a ground plane of the calibrated camera field of view and a backward projected line passing through a center of the calibrated camera and a point on the object 2D image within a focal plane in the 2D image field of view of the video data input at an initial time;

computing a second 3D location of the observed 2D object image via the processor as an intersection between the ground plane and another backward projected line passing through the center of the calibrated camera and the point on the object 2D image within the video data input 2D image field of view focal plane at a second time that is subsequent to the initial time;

determining a heading direction of the object as a function of the calibrating of the camera and a movement of the 2D object image from the computed initial 3D location to the computed second subsequent 3D location;

replacing the 2D object image in the video data input with a one of a plurality of object-type 3D polygonal models that has a projected bounding box that best matches a bounding box of an image blob of the 2D object image relative to others of the 3D polygonal models, the replacing further orienting the selected object-type 3D polygonal model in the determined heading direction, wherein each of the plurality of object-type 3D polygonal models are for an object type and have a projected bounding box ratio that are different from the object types and projected bounding box ratios of others of the 3D polygonal models;

scaling the bounding box of the replacing polygonal 3D model to fit the object image blob bounding box; and

rendering the scaled replacing polygonal 3D model with image features extracted from the 2D image data as a function of the calibrated dimensions of the 3D modeling cube.

2. The method of claim 1, wherein the replacing the 2D object image in the video data input with the one of the plurality of object-type 3D polygonal models that has the projected bounding box that best matches the bounding box of an image blob of the 2D object image relative to others of the 3D polygonal models further comprises:

determining ratios of projected sizes of each of the bounding boxes of each of the plurality of object-type 3D polygonal models to the image blob bounding box;

comparing aspect ratios of each of the bounding boxes of the each of the plurality of object-type 3D polygonal models to an aspect ratio value of the image blob bounding box; and

selecting the object-type 3D polygonal model with the bounding box that has;

a determined ratio of projected size to the image blob bounding box that meets a threshold value; and

an aspect ratio that is more similar to the aspect ratio of the image blob bounding box relative to the aspect ratios of others of the bounding boxes of the other models.

3. The method of claim 2, wherein the step of selecting the object-type 3D polygonal model further comprises:

determining for each of the models weighted sums of their respective determined ratios of projected size to the image blob bounding box and aspect ratios, wherein the aspect ratios are weighted more heavily than the determined ratios of projected size to the image blob bounding box; and

selecting a model having a best weighted sum value as the selected model.

4. The method of claim 2, further comprising:

selecting the model having a best weighted sum value as the selected model from a subset of the models that each have an aspect ratio similarity to the aspect ratio of the image blob bounding box that satisfies a threshold condition.

5. The method of claim 4, further comprising:

selecting one of a single-dimension scaling process and a multi-dimension scaling process as appropriate to the object type of the replacing polygonal 3D model, wherein the single-dimension and multi-dimension scaling processes are appropriate to different ones of the object types of the polygonal 3D model; and

wherein the scaling the bounding box ratio of the replacing polygonal 3D model to correspond to the object image blob bounding box ratio comprises using the selected one of the single-dimension scaling process and the multi-dimension scaling process.

6. The method of claim 5, wherein the selected scaling process is the single-dimension scaling process, and wherein the scaling the bounding box ratio of the replacing polygonal 3D model to correspond to the object image blob bounding box ratio comprises:

determining a first of the spatial dimensions of the projected bounding box of the selected model, the first spatial dimension of the object image blob bounding box, and a first spatial dimension ratio between the determined selected model first spatial dimension and the determined object image blob bounding box first spatial dimension;

scaling the bounding box of the selected model in the first dimension by the determined first spatial dimension ratio to match the object image blob bounding box; and

shifting the selected model so that a location point of the selected model on a boundary box line of the projected bounding box of the selected model that is normal to the first dimension axis is co-located with a corresponding point of the object image blob on a corresponding boundary box line of the object image blob bounding box, wherein the selected model location point is on a back projection line comprising the corresponding point of the object image blob and the center of the calibrated camera.

7. The method of claim 5, wherein the selected scaling process is the multi-dimension scaling process, and wherein the scaling the bounding box ratio of the replacing polygonal 3D model to correspond to the object image blob bounding box ratio comprises:

determining a first dimensional vector of the three spatial dimensions of the 2D object image blob bounding box in image space on the image ground plane aligned with a first dimension axis of the object image blob bounding box;

determining a second dimensional vector of the three spatial dimensions of the 2D object image blob bounding box in image space on the image ground plane through alignment with a second dimension axis of the object image blob bounding box;

determining a heading direction vector as a function of the calibrating of the camera and the movement of the 2D object image from the computed initial 3D location to the computed second subsequent 3D location;

determining a third dimension vector perpendicular to the heading vector and aligned with a third dimension axis of the three spatial dimensions;

projecting the first dimensional vector to the heading direction vector and the third dimension vector to obtain first projected dimension scaling factors for each of the first dimension and the second dimension;

projecting the second dimensional vector to the heading direction vector and the third dimension vector to obtain second projected dimension scaling factors for each of the first dimension and the second dimension;

determining a final scaling factor for the first dimension by summing the first and second projected dimension scaling factors obtained for the first dimension;

determining a final scaling factor for the second dimension by summing the first and second projected dimension scaling factors obtained for the second dimension;

selecting one of the determined final first and second dimension scaling factors as a final third dimension scaling factor; and

scaling each of the three dimensions of the selected model by their respective final first, second and third dimension scaling factors.

8. A system, comprising:

a processing unit, a computer readable memory and a computer readable storage medium;

wherein the processing unit, when executing program instructions stored on the computer readable storage medium via the computer readable memory;

calibrates a 2D image field of view of a video data input of a camera to three spatial dimensions of a 3D modeling cube specified manually by a user via a user interface, wherein each of the 3D modeling cube three spatial dimensions are at right angles with respect to each other of the three spatial dimensions;

in response to an observed image of an object in motion in the 2D image field of view of a video data input, computes an initial 3D location of the observed 2D object image via the processor as an intersection between a ground plane of the calibrated camera field of view and a backward projected line passing through a center of the calibrated camera and a point on the object 2D image within a focal plane in the 2D image field of view of the video data input at an initial time;

computes a second 3D location of the observed 2D object image via the processor as an intersection between the ground plane and another backward projected line passing through the center of the calibrated camera and the point on the object 2D image within the video data input 2D image field of view focal plane at a second time that is subsequent to the initial time;

determines a heading direction of the object as a function of the manual calibration of the camera and a movement of the 2D object image from the computed initial 3D location to the computed second subsequent 3D location;

replaces the 2D object image in the video data input with a one of a plurality of object-type 3D polygonal models that has a projected bounding box that best matches a bounding box of an image blob of the 2D object image relative to others of the 3D polygonal models, the replacing further orienting the selected object-type 3D polygonal model in the determined heading direction, wherein each of the plurality of object-type 3D polygonal models are for an object type and have a projected bounding box ratio that are different from the object types and projected bounding box ratios of others of the 3D polygonal models;

scales the bounding box of the replacing polygonal 3D model to fit the object image blob bounding box; and

renders the scaled replacing polygonal 3D model with image features that are extracted from the 2D image data as a function of the calibrated dimensions of the 3D modeling cube.

9. The system of claim 8, wherein the processing unit, when executing the program instructions stored on the computer readable storage medium via the computer readable memory, further replaces the 2D object image in the video data input with the one of the plurality of object-type 3D polygonal models that has the projected bounding box that best matches the bounding box of an image blob of the 2D object image relative to others of the 3D polygonal models by:

determining ratios of projected sizes of each of the bounding boxes of each of the plurality of object-type 3D polygonal models to the image blob bounding box;

comparing aspect ratios of each of the bounding boxes of the each of the plurality of object-type 3D polygonal models to an aspect ratio value of the image blob bounding box; and

selecting the object-type 3D polygonal model with the bounding box that has;

a determined ratio of projected size to the image blob bounding box that meets a threshold value; and

an aspect ratio that is more similar to the aspect ratio of the image blob bounding box relative to the aspect ratios of others of the bounding boxes of the other models.

10. The system of claim 9, wherein the processing unit, when executing the program instructions stored on the computer readable storage medium via the computer readable memory, selects the object-type 3D polygonal model by:

determining for each of the models sums of their respective determined ratios of projected size to the image blob bounding box and aspect ratios; and

selecting a model having a best sum value from a subset of the models that each have an aspect ratio similarity to the aspect ratio of the image blob bounding box that satisfies a threshold condition.

11. The system of claim 10, wherein the processing unit, when executing the program instructions stored on the computer readable storage medium via the computer readable memory, further:

selects one of a single-dimension scaling process and a multi-dimension scaling process as appropriate to the object type of the replacing polygonal 3D model, wherein the single-dimension and multi-dimension scaling processes are appropriate to different ones of the object types of the polygonal 3D model; and

scales the bounding box ratio of the replacing polygonal 3D model to correspond to the object image blob bounding box ratio by using the selected one of the single-dimension scaling process and the multi-dimension scaling process.

12. The system of claim 11, wherein the selected scaling process is the single-dimension scaling process, and wherein the processing unit, when executing the program instructions stored on the computer-readable storage medium via the computer readable memory, scales the bounding box ratio of the replacing polygonal 3D model to correspond to the object image blob bounding box ratio by:

determining a first of the spatial dimensions of the projected bounding box of the selected model, the first spatial dimension of the object image blob bounding box, and a first spatial dimension ratio between the determined selected model first spatial dimension and the determined object image blob bounding box first spatial dimension;

scaling the bounding box of the selected model in the first dimension by the determined first spatial dimension ratio to match the object image blob bounding box; and

shifting the selected model so that a location point of the selected model on a boundary box line of the projected bounding box of the selected model that is normal to the first dimension axis is co-located with a corresponding point of the object image blob on a corresponding boundary box line of the object image blob bounding box, wherein the selected model location point is on a back projection line comprising the corresponding point of the object image blob and the center of the calibrated camera.

13. The system of claim 11, wherein the selected scaling process is the multi-dimension scaling process, and wherein the processing unit, when executing the program instructions stored on the computer-readable storage medium via the computer readable memory, scales the bounding box ratio of the replacing polygonal 3D model to correspond to the object image blob bounding box ratio by:

determining a first dimensional vector of the three spatial dimensions of the 2D object image blob bounding box in image space on the image ground plane aligned with a first dimension axis of the object image blob bounding box;

determining a second dimensional vector of the three spatial dimensions of the 2D object image blob bounding box in image space on the image ground plane through alignment with a second dimension axis of the object image blob bounding box;

determining a heading direction vector as a function of the calibrating of the camera and the movement of the 2D object image from the computed initial 3D location to the computed second subsequent 3D location;

determining a third dimension vector perpendicular to the heading vector and aligned with a third dimension axis of the three spatial dimensions;

projecting the first dimensional vector to the heading direction vector and the third dimension vector to obtain first projected dimension scaling factors for each of the first dimension and the second dimension;

projecting the second dimensional vector to the heading direction vector and the third dimension vector to obtain second projected dimension scaling factors for each of the first dimension and the second dimension;

determining a final scaling factor for the first dimension by summing the first and second projected dimension scaling factors obtained for the first dimension;

determining a final scaling factor for the second dimension by summing the first and second projected dimension scaling factors obtained for the second dimension;

selecting one of the determined final first and second dimension scaling factors as a final third dimension scaling factor; and

scaling each of the three dimensions of the selected model by their respective final first, second and third dimension scaling factors.

14. An article of manufacture, comprising:

a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising instructions that, when executed by a computer processor, cause the computer processor to;

calibrate a 2D image field of view of a video data input of a camera to three spatial dimensions of a 3D modeling cube specified manually by a user via a user interface, wherein each of the 3D modeling cube three spatial dimensions are at right angles with respect to each other of the three spatial dimensions;

in response to an observed image of an object in motion in the 2D image field of view of a video data input, compute an initial 3D location of the observed 2D object image via the processor as an intersection between a ground plane of the calibrated camera field of view and a backward projected line passing through a center of the calibrated camera and a point on the object 2D image within a focal plane in the 2D image field of view of the video data input at an initial time;

compute a second 3D location of the observed 2D object image via the processor as an intersection between the ground plane and another backward projected line passing through the center of the calibrated camera and the point on the object 2D image within the video data input 2D image field of view focal plane at a second time that is subsequent to the initial time;

determines a heading direction of the object as a function of the manual calibration of the camera and a movement of the 2D object image from the computed initial 3D location to the computed second subsequent 3D location;

replace the 2D object image in the video data input with a one of a plurality of object-type 3D polygonal models that has a projected bounding box that best matches a bounding box of an image blob of the 2D object image relative to others of the 3D polygonal models, the replacing further orienting the selected object-type 3D polygonal model in the determined heading direction, wherein each of the plurality of object-type 3D polygonal models are for an object type and have a projected bounding box ratio that are different from the object types and projected bounding box ratios of others of the 3D polygonal models;

scale the bounding box of the replacing polygonal 3D model to fit the object image blob bounding box; and

render the scaled replacing polygonal 3D model with image features that are extracted from the 2D image data as a function of the calibrated dimensions of the 3D modeling cube.

15. The article of manufacture of claim 14, wherein the computer readable program code instructions, when executed by the computer processor, further cause the computer processor to replace the 2D object image in the video data input with the one of the plurality of object-type 3D polygonal models that has the projected bounding box that best matches the bounding box of an image blob of the 2D object image relative to others of the 3D polygonal models by:

determining ratios of projected sizes of each of the bounding boxes of each of the plurality of object-type 3D polygonal models to the image blob bounding box;

comparing aspect ratios of each of the bounding boxes of the each of the plurality of object-type 3D polygonal models to an aspect ratio value of the image blob bounding box; and

selecting the object-type 3D polygonal model with the bounding box that has;

a determined ratio of projected size to the image blob bounding box that meets a threshold value; and

an aspect ratio that is more similar to the aspect ratio of the image blob bounding box relative to the aspect ratios of others of the bounding boxes of the other models.

16. The article of manufacture of claim 15, wherein the computer readable program code instructions, when executed by the computer processor, further cause the computer processor to select the object-type 3D polygonal model by:

determining for each of the models sums of their respective determined ratios of projected size to the image blob bounding box and aspect ratios; and

selecting a model having a best sum value from a subset of the models that each have an aspect ratio similarity to the aspect ratio of the image blob bounding box that satisfies a threshold condition.

17. The article of manufacture of claim 16, wherein the computer readable program code instructions, when executed by the computer processor, further cause the computer processor to:

select one of a single-dimension scaling process and a multi-dimension scaling process as appropriate to the object type of the replacing polygonal 3D model, wherein the single-dimension and multi-dimension scaling processes are appropriate to different ones of the object types of the polygonal 3D model; and

scale the bounding box ratio of the replacing polygonal 3D model to correspond to the object image blob bounding box ratio by using the selected one of the single-dimension scaling process and the multi-dimension scaling process.

18. The article of manufacture of claim 17, wherein the selected scaling process is the single-dimension scaling process, and wherein the computer readable program code instructions, when executed by the computer processor, further cause the computer processor to scale the bounding box ratio of the replacing polygonal 3D model to correspond to the object image blob bounding box ratio by:

determining a first of the spatial dimensions of the projected bounding box of the selected model, the first spatial dimension of the object image blob bounding box, and a first spatial dimension ratio between the determined selected model first spatial dimension and the determined object image blob bounding box first spatial dimension;

scaling the bounding box of the selected model in the first dimension by the determined first spatial dimension ratio to match the object image blob bounding box; and

shifting the selected model so that a location point of the selected model on a boundary box line of the projected bounding box of the selected model that is normal to the first dimension axis is co-located with a corresponding point of the object image blob on a corresponding boundary box line of the object image blob bounding box, wherein the selected model location point is on a back projection line comprising the corresponding point of the object image blob and the center of the calibrated camera.

19. The article of manufacture of claim 18, wherein the selected scaling process is the multi-dimension scaling process, and wherein the computer readable program code instructions, when executed by the computer processor, further cause the computer processor to scale the bounding box ratio of the replacing polygonal 3D model to correspond to the object image blob bounding box ratio by:

determining a first dimensional vector of the three spatial dimensions of the 2D object image blob bounding box in image space on the image ground plane aligned with a first dimension axis of the object image blob bounding box;

determining a second dimensional vector of the three spatial dimensions of the 2D object image blob bounding box in image space on the image ground plane through alignment with a second dimension axis of the object image blob bounding box;

determining a heading direction vector as a function of the calibrating of the camera and the movement of the 2D object image from the computed initial 3D location to the computed second subsequent 3D location;

determining a third dimension vector perpendicular to the heading vector and aligned with a third dimension axis of the three spatial dimensions;

projecting the first dimensional vector to the heading direction vector and the third dimension vector to obtain first projected dimension scaling factors for each of the first dimension and the second dimension;

projecting the second dimensional vector to the heading direction vector and the third dimension vector to obtain second projected dimension scaling factors for each of the first dimension and the second dimension;

determining a final scaling factor for the first dimension by summing the first and second projected dimension scaling factors obtained for the first dimension;

determining a final scaling factor for the second dimension by summing the first and second projected dimension scaling factors obtained for the second dimension;

selecting one of the determined final first and second dimension scaling factors as a final third dimension scaling factor; and

scaling each of the three dimensions of the selected model by their respective final first, second and third dimension scaling factors.

20. A method of providing a service for modeling objects within two-dimensional (2D) video data by three-dimensional (3D) models as a function of object type and motion, the method comprising providing:

a camera calibration interface that enables a user to calibrate a 2D image field of view of a video data input of a camera to three spatial dimensions of a 3D modeling cube specified manually by the user, wherein each of the 3D modeling cube three spatial dimensions are at right angles with respect to each other of the three spatial dimensions;

a 3D location determiner that, in response to an observed image of an object in motion in the 2D image field of view of a video data input, computes an initial 3D location of the observed 2D object image via the processor as an intersection between a ground plane of the calibrated camera field of view and a backward projected line passing through a center of the calibrated camera and a point on the object 2D image within a focal plane in the 2D image field of view of the video data input at an initial time; and

computes a second 3D location of the observed 2D object image via the processor as an intersection between the ground plane and another backward projected line passing through the center of the calibrated camera and the point on the object 2D image within the video data input 2D image field of view focal plane at a second time that is subsequent to the initial time;

a heading direction determiner that determines a heading direction of the object as a function of the manual calibration of the camera and a movement of the 2D object image from the computed initial 3D location to the computed second subsequent 3D location;

a model selector that replaces the 2D object image in the video data input with a one of a plurality of object-type 3D polygonal models that has a projected bounding box that best matches a bounding box of an image blob of the 2D object image relative to others of the 3D polygonal models, the replacing further orienting the selected object-type 3D polygonal model in the determined heading direction, wherein each of the plurality of object-type 3D polygonal models are for an object type and have a projected bounding box ratio that are different from the object types and projected bounding box ratios of others of the 3D polygonal models;

a model scaler that scales the bounding box of the replacing polygonal 3D model to fit the object image blob bounding box; and

a feature extractor that renders the scaled replacing polygonal 3D model with image features that are extracted from the 2D image data as a function of the calibrated dimensions of the 3D modeling cube.

21. The method of claim 20, wherein the model selector replaces the 2D object image in the video data input with the one of the plurality of object-type 3D polygonal models that has the projected bounding box that best matches the bounding box of an image blob of the 2D object image relative to others of the 3D polygonal models by:

determining ratios of projected sizes of each of the bounding boxes of each of the plurality of object-type 3D polygonal models to the image blob bounding box;

comparing aspect ratios of each of the bounding boxes of the each of the plurality of object-type 3D polygonal models to an aspect ratio value of the image blob bounding box; and

selecting the object-type 3D polygonal model with the bounding box that has;

a determined ratio of projected size to the image blob bounding box that meets a threshold value; and

an aspect ratio that is more similar to the aspect ratio of the image blob bounding box relative to the aspect ratios of others of the bounding boxes of the other models.

22. The method of claim 21, wherein the model selector selects the object-type 3D polygonal model by:

determining for each of the models sums of their respective determined ratios of projected size to the image blob bounding box and aspect ratios; and

selecting a model having a best sum value from a subset of the models that each have an aspect ratio similarity to the aspect ratio of the image blob bounding box that satisfies a threshold condition.

23. The method of claim 22, wherein the model scaler:

selects one of a single-dimension scaling process and a multi-dimension scaling process as appropriate to the object type of the replacing polygonal 3D model, wherein the single-dimension and multi-dimension scaling processes are appropriate to different ones of the object types of the polygonal 3D model; and

scales the bounding box ratio of the replacing polygonal 3D model to correspond to the object image blob bounding box ratio by using the selected one of the single-dimension scaling process and the multi-dimension scaling process.

24. The method of claim 23, wherein the model scaler, when selecting the single-dimension scaling process, scales the bounding box ratio of the replacing polygonal 3D model to correspond to the object image blob bounding box ratio by:

determining a first of the spatial dimensions of the projected bounding box of the selected model, the first spatial dimension of the object image blob bounding box, and a first spatial dimension ratio between the determined selected model first spatial dimension and the determined object image blob bounding box first spatial dimension;

scaling the bounding box of the selected model in the first dimension by the determined first spatial dimension ratio to match the object image blob bounding box; and

shifting the selected model so that a location point of the selected model on a boundary box line of the projected bounding box of the selected model that is normal to the first dimension axis is co-located with a corresponding point of the object image blob on a corresponding boundary box line of the object image blob bounding box, wherein the selected model location point is on a back projection line comprising the corresponding point of the object image blob and the center of the calibrated camera.

25. The method of claim 23, wherein the model scaler, when selecting the multi-dimension scaling process, scales the bounding box ratio of the replacing polygonal 3D model to correspond to the object image blob bounding box ratio by:

determining a first dimensional vector of the three spatial dimensions of the 2D object image blob bounding box in image space on the image ground plane aligned with a first dimension axis of the object image blob bounding box;

determining a second dimensional vector of the three spatial dimensions of the 2D object image blob bounding box in image space on the image ground plane through alignment with a second dimension axis of the object image blob bounding box;

determining a heading direction vector as a function of the calibrating of the camera and the movement of the 2D object image from the computed initial 3D location to the computed second subsequent 3D location;

determining a third dimension vector perpendicular to the heading vector and aligned with a third dimension axis of the three spatial dimensions;

projecting the first dimensional vector to the heading direction vector and the third dimension vector to obtain first projected dimension scaling factors for each of the first dimension and the second dimension;

projecting the second dimensional vector to the heading direction vector and the third dimension vector to obtain second projected dimension scaling factors for each of the first dimension and the second dimension;

determining a final scaling factor for the first dimension by summing the first and second projected dimension scaling factors obtained for the first dimension;

determining a final scaling factor for the second dimension by summing the first and second projected dimension scaling factors obtained for the second dimension;

selecting one of the determined final first and second dimension scaling factors as a final third dimension scaling factor; and

scaling each of the three dimensions of the selected model by their respective final first, second and third dimension scaling factors.