IP Library › Granted Patent US 12,530,791
Granted Patent B2
US 12,530,791 · App. 18/331,203 · Granted Jan 20, 2026

Methods and systems for enhancing depth perception of a non-visible spectrum image of a scene

Inventor: Yoav Ophir (Haifa, IL)
Assignee: ELBIT SYSTEMS LTD.
G06T7/586G06T11/00G06T2207/10048G06T2207/20092
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Quick Facts
Patent No.
US 12,530,791
App. No.
18/331,203
Granted
Jan 20, 2026
Kind
B2
Abstract

A method and system for providing depth perception to a two-dimensional (2D) representation of a given three-dimensional (3D) object within a 2D non-visible spectrum image of a scene is provided. The method comprises: capturing the 2D non-visible spectrum image at a capture time, by at least one non-visible spectrum sensor; obtaining 3D data regarding the given 3D object independently of the 2D non-visible spectrum image; generating one or more depth cues based on the 3D data; applying the depth cues on the 2D representation to generate a depth perception image that provides the depth perception to the 2D representation; and displaying the depth perception image.

Claims (51)

1 . A method for providing depth perception to a two-dimensional (2D) representation of a given three-dimensional (3D) object within a 2D non-visible spectrum image of a scene, the method comprising:

capturing the 2D non-visible spectrum image at a capture time, by at least one non-visible spectrum sensor;

obtaining 3D data regarding the given 3D object independently of the 2D non-visible spectrum image;

generating one or more depth cues based on the 3D data;

applying the depth cues on the 2D representation to generate a depth perception image that provides the depth perception to the 2D representation; and

displaying the depth perception image.

2 . The method of claim 1 , wherein the 3D data is a priori data regarding coordinates of a fixed coordinate system established in space that are associated with the given 3D object, the a priori data being available prior to the capture time; and

wherein the depth cues are generated based on the a priori data and an actual position and orientation of the non-visible spectrum sensor relative to the fixed coordinate system at the capture time.

3 . The method of claim 1 , wherein the 3D data is one or more readings by an additional sensor that is distinct from the non-visible spectrum sensor; and

wherein the depth cues are generated based on the readings and a first actual position and orientation of the non-visible spectrum sensor at the capture time relative to a second actual position and orientation of the additional sensor at a second time of the readings.

4 . The method of claim 1 , further comprising:

recording the 2D non-visible spectrum image to provide a recording of the 2D non-visible spectrum image;

wherein the depth cues are applied on the 2D representation within the 2D non-visible spectrum image as recorded.

5 . The method of claim 1 , wherein the depth cues include one or more of the following:

(a) one or more shadows;

(b) a virtual object; or

(c) contour lines.

6 . The method of claim 5 , wherein at least some of the shadows are generated by one or more virtual light sources.

7 . The method of claim 6 , further comprising:

selecting one or more selected light sources of the virtual light sources.

8 . The method of claim 7 , wherein, for at least one selected light source of the selected light sources, one or more parameters of the at least one selected light source are defined by a user, the one or more parameters including a position and an orientation of the at least one selected light source.

9 . The method of claim 5 , wherein the virtual object is distinguishable from the 2D representation.

10 . A system for providing depth perception to a two-dimensional (2D) representation of a given three-dimensional (3D) object within a 2D non-visible spectrum image of a scene, the system comprising:

at least one non-visible spectrum sensor configured to capture the 2D non-visible spectrum image at a capture time; and

a processing circuitry configured to:

obtain 3D data regarding the given 3D object independently of the 2D non-visible spectrum image;

generate one or more depth cues based on the 3D data;

apply the depth cues on the 2D representation to generate a depth perception image that provides the depth perception to the 2D representation; and

display the depth perception image.

11 . The system of claim 10 , wherein the 3D data is a priori data regarding coordinates of a fixed coordinate system established in space that are associated with the given 3D object, the a priori data being available prior to the capture time; and

wherein the depth cues are applied based on the a priori data and an actual position and orientation of the non-visible spectrum sensor relative to the fixed coordinate system at the capture time.

12 . The system of claim 10 , wherein the 3D data is one or more readings by an additional sensor that is distinct from the non-visible spectrum sensor; and

wherein the depth cues are generated based on the readings and a first actual position and orientation of the non-visible spectrum sensor at the capture time relative to a second actual position and orientation of the additional sensor at a second time of the readings.

13 . The system of claim 10 , wherein the processing circuitry is further configured to:

record the 2D non-visible spectrum image to provide a recording of the 2D non-visible spectrum image;

wherein the depth cues are applied on the 2D non-visible spectrum image as recorded.

14 . The system of claim 10 , wherein the depth cues include one or more of the following:

(a) one or more shadows;

(b) a virtual object; or

(c) contour lines.

15 . The system of claim 14 , wherein at least some of the shadows are generated by one or more virtual light sources.

16 . The system of claim 15 , wherein the processing circuitry is further configured to:

select one or more selected light sources of the virtual light sources.

17 . The system of claim 16 , wherein, for at least one selected light source of the selected light sources, one or more parameters of the at least one selected light source are defined by a user of the system, the one or more parameters including a position and an orientation of the at least one selected light source.

18 . The system of claim 14 , wherein the virtual object is distinguishable from the 2D representation.

19 . A non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, executable by processing circuitry of a computer to perform a method for providing depth perception to a two-dimensional (2D) representation of a given three-dimensional (3D) object within a 2D non-visible spectrum image of a scene, the method comprising:

capturing the 2D non-visible spectrum image at a capture time, by at least one non-visible spectrum sensor;

obtaining 3D data regarding the given 3D object independently of the 2D non-visible spectrum image;

generating one or more depth cues based on the 3D data;

applying the depth cues on the 2D representation to generate a depth perception image that provides the depth perception to the 2D representation; and

displaying the depth perception image.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 8, 2023
From: OPHIR, YOAV
To: ELBIT SYSTEMS LTD.
Reel/Frame 063920/0649 →
Priority Claims (1)
IL 279342 · Dec 9, 2020 · national
Continuity (3)
Continuation PCTIL2021051467 · Dec 9, 2021
Provisional Application 63287092 · Dec 8, 2021
Related Publication 20230326058A1 · Oct 12, 2023
References Cited (26)
US 6157733A · Swain · 2000 [cited by applicant]
US 6252982B1 · Haisma et al. · 2001 [cited by applicant]
US 9798388B1 · Murali · 2017 [cited by examiner]
US 9995936B1 · Macannuco et al. · 2018 [cited by applicant]
US 20030014212A1 · Ralston · 2003 [cited by applicant]
US 20050285356A1 · Malit · 2005 [cited by examiner]
US 20080123960A1 · Kim et al. · 2008 [cited by applicant]
US 20100110308A1 · Nicholson · 2010 [cited by examiner]
US 20100111370A1 · Black · 2010 [cited by examiner]
US 20120323365A1 · Taylor · 2012 [cited by examiner]
US 20130278597A1 · Sasaki · 2013 [cited by applicant]
US 20150049308A1 · Mealing · 2015 [cited by examiner]
US 20150208054A1 · Michot · 2015 [cited by applicant]
US 20150296200A1 · Grauer · 2015 [cited by examiner]
US 20160343169A1 · Mullins · 2016 [cited by examiner]
US 20160371884A1 · Benko · 2016 [cited by examiner]
US 20160379405A1 · Baca · 2016 [cited by examiner]
US 20170115395A1 · Grauer · 2017 [cited by examiner]
US 20180176541A1 · Abbas · 2018 [cited by examiner]
US 20190012828A1 · Jung et al. · 2019 [cited by applicant]
US 20190122425A1 · Sheffield · 2019 [cited by examiner]
US 20190170510A1 · Robinson · 2019 [cited by examiner]
US 20190360810A1 · Johnson et al. · 2019 [cited by applicant]
CN 111145122A · 2020 [cited by applicant]
EP 2031559A1 · 2009 [cited by applicant]
Daniel Weiskopf & Thomas Ertl (2002) Real-Time Depth-Cueing beyond Fogging, Journal of Graphics Tools, 7:4, 83-90, DOI: 10.1080/10867651.2002.10487575. [cited by applicant]