IP Library Granted Patent US 12,354,366
Granted Patent B2
US 12,354,366 · App. 17/499,291 · Granted Jul 8, 2025

Full image detection for vehicle navigation

Inventors: Yaakov Shambik (Jerusalem, IL); Ohad Chitrit (Givatayim, IL); Eran Malach (Jerusalem, IL); Dan Kufra (Jerusalem, IL)
Assignee: Mobileye Vision Technologies Ltd.
G06V20/56G05D1/0246G05D1/249G06T7/20G06T7/50G06T7/70G06V20/58B60R2011/0026B60R11/04B60W60/0027B60W2420/403B60W2554/402B60W2554/4026B60W2554/4043B60W2554/801G06T2207/20084G06T2207/30252G06V2201/08
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Quick Facts
Patent No.
US 12,354,366
App. No.
17/499,291
Granted
Jul 8, 2025
Kind
B2
Abstract

Systems and methods are provided for vehicle navigation. In one implementation, at least one processing device may receive, from a camera of the host vehicle, at least one captured image representative of an environment of the host vehicle. The processing device may analyze one or more pixels of the at least one captured image to determine whether the one or more pixels represent at least a portion of a target vehicle. For pixels determined to represent at least a portion of the target vehicle, the processing device may determine one or more estimated distance values from the one or more pixels to at least one edge of a face of the target vehicle; and generate, based on the analysis of the one or more pixels, including the determined one or more distance values associated with the one or more pixels, at least a portion of a boundary relative to the target vehicle.

Claims (48)

1. A navigation system for a host vehicle, the system comprising:

at least one processor comprising circuitry and a memory, wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to:

receive at least one image captured by a camera of the host vehicle, the at least one image being representative of an environment of the host vehicle;

analyze one or more pixels of the at least one image to determine whether the one or more pixels represent at least a portion of a target vehicle, and for pixels determined to represent at least a portion of the target vehicle, determine one or more estimated distance values from the one or more pixels to at least one edge of a face of the target vehicle;

determine, based on analysis of the at least one image, whether the target vehicle is carried by another vehicle or a trailer, wherein analyzing the at least one image includes inputting the at least one image into a trained system configured to determine whether vehicles represented in images are carried vehicles; and

generate, based on the analysis of the one or more pixels, including the determined one or more distance values associated with the one or more pixels and the determination whether the target vehicle is carried by another vehicle or a trailer, at least a portion of a boundary relative to the target vehicle.

2. The navigation system of claim 1 , wherein the one or more distance values are measured in pixels.

3. The navigation system of claim 1 , wherein the one or more distance values correspond to real world distances measured relative to the target vehicle.

4. The navigation system of claim 1 , wherein the one or more distance values include a distance from a particular pixel to at least one of a forward edge, rearward edge, side edge, top edge, or bottom edge of the target vehicle.

5. The navigation system of claim 1 , wherein the memory further includes instructions that when executed by the circuitry cause the at least one processor to determine an orientation of the at least a portion of the boundary generated relative to the target vehicle.

6. The navigation system of claim 5 , wherein the memory further includes instructions that when executed by the circuitry cause the at least one processor to determine a navigational action for the host vehicle based on the determined orientation of the at least a portion of the boundary and cause the host vehicle to implement the determined navigational action.

7. The navigation system of claim 5 , wherein the determined orientation is indicative of a maneuver by the target vehicle toward a path of the host vehicle.

8. The navigation system of claim 5 , wherein the determined orientation is indicative of a lateral motion by the target vehicle relative to the host vehicle.

9. The navigation system of claim 1 , wherein the memory further includes instructions that when executed by the circuitry cause the at least one processor to determine whether the one or more pixels include a bounding pixel that includes a representation of at least a portion of the at least one edge of the target vehicle.

10. The navigation system of claim 1 , wherein the analysis is performed for every pixel of the at least one image.

11. The navigation system of claim 1 , wherein the analysis is performed for every pixel of a target vehicle candidate region identified relative to the at least one image.

12. The navigation system of claim 1 , wherein the portion of the boundary includes at least a portion of a bounding box.

13. The navigation system of claim 1 , wherein the memory further includes instructions that when executed by the circuitry cause the at least one processor to determine a distance of the portion of the boundary to the host vehicle and cause the vehicle to implement a navigational action based at least on the determined distance.

14. The navigation system of claim 1 , wherein the trained system includes one or more neural networks.

15. The navigation system of claim 1 , wherein at least a portion of at least one edge of the target vehicle is not represented in the at least one image.

16. The navigation system of claim 1 , wherein one or more edges of the target vehicle are not represented in the at least one image.

17. The navigation system of claim 1 , wherein the memory further includes instructions that when executed by the circuitry cause the at least one processor to not determine a boundary for a carried vehicle.

18. The navigation system of claim 1 , wherein the memory further includes instructions that when executed by the circuitry cause the at least one processor to determine based on analysis of the at least one image whether the target vehicle is included in a representation of a reflection in the at least one image.

19. The navigation system of claim 18 , wherein the at least one processor is further programmed to not determine a boundary for a vehicle reflection.

20. The navigation system of claim 1 , wherein the memory further includes instructions that when executed by the circuitry cause the at least one processor to output a type of the target vehicle.

21. The navigation system of claim 20 , wherein the type of the target vehicle is based at least on a size of the portion of the boundary.

22. The navigation system of claim 20 , wherein the type of the target vehicle is based, at least in part, on a number of pixels included within the boundary.

23. The navigation system of claim 20 , wherein the type of the target vehicle includes at least one of a bus, truck, bike, motorcycle, or car.

24. A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, are configured to cause at least one processor to:

receive at least one image captured by a camera of a host vehicle, the at least one image being representative of an environment of the host vehicle;

analyze one or more pixels of the at least one image to determine whether the one or more pixels represent at least a portion of a target vehicle, and for pixels determined to represent at least a portion of the target vehicle, determine one or more estimated distance values from the one or more pixels to at least one edge of a face of the target vehicle;

determine, based on analysis of the at least one image, whether the target vehicle is carried by another vehicle or a trailer, wherein analyzing the at least one image includes inputting the at least one image into a trained system configured to determine whether vehicles represented in images are carried vehicles; and

generate, based on the analysis of the one or more pixels, including the determined one or more distance values associated with the one or more pixels and the determination whether the target vehicle is carried by another vehicle or a trailer, at least a portion of a boundary relative to the target vehicle.

25. The non-transitory computer-readable medium of claim 24 , further storing instructions that, when executed by at least one processor, are configured to cause at least one processor to determine an orientation of the at least a portion of the boundary generated relative to the target vehicle.

26. The non-transitory computer-readable medium of claim 25 , further storing instructions that, when executed by at least one processor, are configured to cause at least one processor to determine a navigational action for the host vehicle based on the determined orientation of the at least a portion of the boundary and cause the vehicle to implement the determined navigational action.

27. The non-transitory computer-readable medium of claim 25 , wherein the determined orientation is indicative of a maneuver by the target vehicle toward a path of the host vehicle.

28. The non-transitory computer-readable medium of claim 25 , wherein the determined orientation is indicative of a lateral motion by the target vehicle relative to the host vehicle.

29. The non-transitory computer-readable medium of claim 24 , further storing instructions that, when executed by at least one processor, are configured to cause at least one processor to determine a distance of the portion of the boundary to the host vehicle and cause the vehicle to implement a navigational action based at least on the determined distance.

30. A method for navigating a host vehicle, the method comprising:

receiving at least one image captured by a camera of a host vehicle, the at least one image being representative of an environment of the host vehicle;

analyzing one or more pixels of the at least one image to determine whether the one or more pixels represent at least a portion of a target vehicle, and for pixels determined to represent at least a portion of the target vehicle, determine one or more estimated distance values from the one or more pixels to at least one edge of a face of the target vehicle;

determining, based on analysis of the at least one image, whether the target vehicle is carried by another vehicle or a trailer, wherein analyzing the at least one image includes inputting the at least one image into a trained system configured to determine whether vehicles represented in images are carried vehicles; and

generating, based on the analysis of the one or more pixels, including the determined one or more distance values associated with the one or more pixels and the determination whether the target vehicle is carried by another vehicle or a trailer, at least a portion of a boundary relative to the target vehicle.

31. The method of claim 30 , further comprising determining an orientation of the at least a portion of the boundary generated relative to the target vehicle.

32. The method of claim 31 , further comprising determining a navigational action for the host vehicle based on the determined orientation of the at least a portion of the boundary and causing the vehicle to implement the determined navigational action.

33. The method of claim 31 , wherein the determined orientation is indicative of a maneuver by the target vehicle toward a path of the host vehicle.

34. The method of claim 31 , wherein the determined orientation is indicative of a lateral motion by the target vehicle relative to the host vehicle.

35. The method of claim 30 , further comprising determining a distance of the portion of the boundary to the host vehicle and causing the vehicle to implement a navigational action based at least on the determined distance.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 12, 2021
From: SHAMBIK, YAAKOV; CHITRIT, OHAD; MALACH, ERAN; KUFRA, DAN
To: MOBILEYE VISION TECHNOLOGIES LTD.
Reel/Frame 057767/0680 →
Continuity (5)
Continuation PCTUS2020034231 · May 22, 2020
Provisional Application 62976059 · Feb 13, 2020
Provisional Application 62957009 · Jan 3, 2020
Provisional Application 62852761 · May 24, 2019
Related Publication 20220027642A1 · Jan 27, 2022
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