Methods and systems for image processing in a multiview video system

• US 8,264,542 B2
• Filed: 09/04/2008
• Issued: 09/11/2012
• Est. Priority Date: 12/31/2007
• Status: Expired due to Fees

• Current Assignee: Industrial Technology Research Institute
• Original Assignee: Industrial Technology Research Institute
• Inventors: Lee, Kual-Zheng, Jou, Fan-Di, Chen, Hung-Ming
• Primary Examiner(s): Chan, Wing
• Assistant Examiner(s): KATSIKIS, KOSTAS J
• Application Number:
  US12/204,163
• Publication Number:
  US 20090167866A1
• Time in Patent Office: 1,468 Days
• Field of Search: 348/153, 348/159, 348/169, 348/223, 382/154, 382/162, 382/167, 382/168, 382/254
• US Class Current: 348/159
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30236 Traffic on road, railway or crossing
• CPC Class Codes: G06T 7/292 Multi-camera tracking
• CPC Class Codes: G06V 10/25 Determination of region of interest [ROI] or a volume of interest [VOI]

Abstract

A system for image processing is provided. The system includes a region of interest (ROI) module receiving video from a camera and detects a ROI(s) in a first image. A lookup table generates a value responsive to block type for a first vanishing point (VP). A labeling module identifies a point “p” most close to the first VP, a point “q” most remote to the first VP and a length “h” between “p” and “q” in each ROI(s), and generates information on p, q and h. Another lookup table generates information on p′, q′ and h′, wherein p′ is a point most close to a second VP, q′ is a point most remote to the second VP and h′ is a length between p′ and q′ in ROI(s) in the second image. A transforming module transforms ROI(s) in the first image into an ROI in the second image.

Claims

1. An apparatus for image processing in a multiview video environment comprising:

one or more processors; and

one or more memories including software configured to, with the one or more processors, cause the apparatus to perform at least the following;

receive first video signals from a first camera and detect at least one region of interest (ROI) in a first image related to the first video signals;

utilize a first lookup table to generate an attribute value in response to a type of a block, wherein the type of a block is related to a first vanishing point defined in the first image;

identify a first point “

p”

most close to the first vanishing point, a second point “

q”

most remote to the first vanishing point and a length “

h”

between the first point “

p” and

the second point “

q”

in each of the at least one ROI, and generate first information on p, q and h;

utilize a second lookup table to generate second information on p′

, q′ and

h′

in response to the first information, wherein p′

is a first point most close to a second vanishing point defined in a second image related to a second camera, q′

is a second point most remote to the second vanishing point and h′

is a length between the first point p′ and

the second point q′

in each of at least one ROI in the second image; and

transform each of the at least one ROI in the first image into an ROI in the second image based on the second lookup table.

2. The apparatus of claim 1, wherein the identify of p, q and h and generate the first information of p, q and h, further causes the apparatus to:

divide each of the at least one ROI in the first image into a number of blocks; and

assign an attribute value to the blocks in each of the at least one ROI in the first image based on the first lookup table.

3. The apparatus of claim 1, wherein the identify of p, q and h and generate the first information of p, q and h, further causes the apparatus to:

identify the number of blocks related to an object in one of the at least one ROI in the first image.

4. The apparatus of claim 1, wherein the one or more memories and software are configured to, with the one or more processors, cause the apparatus to:

utilize the second lookup table to generate third information on p″

, q″ and

h″

in response to the first information, wherein p″

is a first point most close to a third vanishing point defined in a third image related to a third camera, q″

is a second point most remote to the second vanishing point and h″

is a length between the first point p″ and

the second point q″

in each of at least one ROI in the third image.

5. The apparatus of claim 1, wherein the first video signals include one of non-compressed video signals and compressed video signals.

6. A system for image processing in a multiview video environment, the system comprising:

a number of cameras C₁ to C_N, N being a positive integer;

an apparatus comprising one or more processors and one or more memories including software configured to, with the one or more processors, cause the apparatus to perform at least the following;

receive first video signals from the camera C₁ and detect at least one ROI in a first image related to the first video signals;

utilize a first lookup table to generate an attribute value in response to a type of a block, wherein the type of a block is related to a first vanishing point defined in the first image;

identify a first point “

p”

most close to the first vanishing point and a second point “

q”

most remote to the first vanishing point and a length “

h”

between the first point “

p” and

the second point “

q”

in each of the at least one ROI, and generate first information on p, q and h;

utilize a second lookup table to generate second information on p′

, q′ and

h′

in response to the first information, wherein p′

is a first point most close to a second vanishing point defined in a second image related to each of the cameras C₂ to C_N, q′

is a second point most remote to the second vanishing point and h′

is a length between the first point p′ and

the second point q′

in each of at least one ROI in the second image; and

receive the first information and transform each of the at least one ROI in the first image into an ROI in the second image related to each of the cameras C₂ to C_N based on the second lookup table.

7. The system of claim 6, wherein the identify of p, q and h and generate the first information of p, q and h, further causes the apparatus to:

divide each of the at least one ROI in the first image into a number of blocks and assign an attribute value to the blocks in each of the at least one ROI in the first image based on the first lookup table.

8. The system of claim 6, wherein the identify of p, q and h and generate the first information of p, q and h, further causes the apparatus to:

identify the number of blocks related to an object in one of the at least one ROI in the first image.

9. The system of claim 6 further comprising a number of video encoders E₁ to E_N to respectively receive video signals from the cameras C₁ to C_N.

10. The system of claim 6, wherein the first video signals include one of non-compressed video signals and compressed video signals.

11. A method for image processing in a multiview video environment including a first camera and a second camera, the method comprising:

receiving first video signals from the first camera;

identifying at least one region of interest (ROI) in a first image related to the first video signals;

configuring a first lookup table, wherein the first lookup table generates an attribute value in response to a type of a block, wherein the type of a block is related to a first vanishing point defined in the first image;

identifying a first point “

p”

most close to the first vanishing point, a second point “

q”

most remote to the first vanishing point and a length “

h”

between the first point “

p” and

the second point “

q”

in each of the at least one ROI, and generating first information on p, q and h;

configuring a second lookup table, wherein the second lookup table generates second information on p′

, q′ and

h′

in response to the first information, wherein p′

is a first point most close to a second vanishing point defined in a second image related to the second camera, q′

is a second point most remote to the second vanishing point and h′

is a length between the first point p′ and

the second point q′

in each of at least one ROI in the second image; and

transforming each of the at least one ROI in the first image into an ROI in the second image based on the second lookup table.

12. The method of claim 11, wherein the identifying of p, q and h and generating the first information of p, q and h, further comprising dividing each of the at least one ROI in the first image into a number of blocks and assign an attribute value to the blocks in each of the at least one ROI in the first image based on the first lookup table.

13. The method of claim 11, wherein the identifying of p, q and h and generating the first information of p, q and h, further comprising identifying the number of blocks related to an object in one of the at least one ROI in the first image.

14. The method of claim 11 further comprising:

utilize the second lookup table to generate third information on p″

, q″ and

h″

in response to the first information, wherein p″

is a first point most close to a third vanishing point defined in a third image related to a third camera, q″

is a second point most remote to the second vanishing point and h″

is a length between the first point p″ and

the second point q″

in each of at least one ROI in the third image.

15. The method of claim 11, wherein the first video signals include one of non-compressed video signals and compressed video signals.

16. A method for image processing in a multiview video environment, the method comprising:

providing a number of cameras C₁ to C_N, N being a positive integer;

receiving first video signals from the camera C₁;

detect at least one region of interest (ROI) in a first image related to the first video signals;

configuring a first lookup table, wherein the first lookup table generates an attribute value in response to a type of a block, wherein the type of a block is related to a first vanishing point defined in the first image;

identifying a first point “

p”

most close to the first vanishing point and a second point “

q”

most remote to the first vanishing point and a length “

h”

between the first point “

p” and

the second point “

q”

in each of the at least one ROI, and generate first information on p, q and h;

configuring a second lookup table, wherein the second lookup table generates second information on p′

, q′ and

h′

in response to the first information, wherein p′

is a first point most close to a second vanishing point defined in a second image related to each of the cameras C₂ to C_N, q′

is a second point most remote to the second vanishing point and h′

is a length between the first point p′ and

the second point q′

in each of at least one ROI in the second image; and

receiving the first information and transforming each of the at least one ROI in the first image into an ROI in the second image related to each of the cameras C₂ to C_N based on the second lookup table.

17. The method of claim 16, wherein the identifying of p, q and h and generating the first information of p, q and h, further comprising dividing each of the at least one ROI in the first image into a number of blocks and assign an attribute value to the blocks in each of the at least one ROI in the first image based on the first lookup table.

18. The method of claim 16, wherein the identifying of p, q and h and generating first information of p, q and h, further comprising identifying the number of blocks related to an object in one of the at least one ROI in the first image.

19. The method of claim 16 further comprising a number of video encoders E₁ to E_N to respectively receive video signals from the cameras C₁ to C_N.

20. The method of claim 16, wherein the first video signals include one of non-compressed video signals and compressed video signals.