Methods and apparatus to capture photographs using mobile devices

• US 10,735,645 B2
• Filed: 10/18/2018
• Issued: 08/04/2020
• Est. Priority Date: 06/18/2015
• Status: Active Grant

• Current Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Original Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Inventors: Garcia Morate, Diego, Hurtado Garcia, Antonio, Tovar Velasco, Javier, Barrales Ruiz, Carlos
• Primary Examiner(s): Chen, Chiawei
• Application Number:
  US16/164,201
• Publication Number:
  US 20190052801A1
• Time in Patent Office: 656 Days
• CPC Class Codes: G06T 2207/30168 Image quality inspection
• CPC Class Codes: G06T 2207/30244 Camera pose
• CPC Class Codes: G06T 3/4038 Image mosaicing, e.g. composing plane images from plane sub-images
• CPC Class Codes: G06T 5/73 Deblurring; Sharpening
• CPC Class Codes: G06T 7/0002 Inspection of images, e.g. flaw detection
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06V 10/16 using multiple overlapping images; Image stitching
• CPC Class Codes: G06V 10/17 using hand-held instruments
• CPC Class Codes: G06V 10/245 by locating a pattern; Special marks for positioning
• CPC Class Codes: H04N 23/635 Region indicators; Field of view indicators
• CPC Class Codes: H04N 23/64 Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image
• CPC Class Codes: H04N 23/6811 based on the image signal

Abstract

Methods and apparatus to capture photographs using mobile devices are disclosed. An example apparatus includes a photograph capturing controller to capture a photograph with a mobile device. The apparatus further includes a blurriness analyzer to determine a probability of blurriness of the photograph. The example apparatus also includes a photograph capturing interface to prompt a user to capture a new photograph when the probability of blurriness exceeds a blurriness threshold.

Claims

1. An apparatus comprising:

a photograph capturing controller to capture a first photograph with a mobile device;

a blurriness analyzer to determine a probability of blurriness of the first photograph at a time when the first photograph is captured, the probability of blurriness based on an analysis of a subset of multiple areas of the first photograph, the subset excluding a region of the first photograph associated with an auto-focus operation of the mobile device; and

a photograph capturing interface to prompt a user, prior to displaying the first photograph to the user, to capture a new photograph to replace the first photograph when the probability of blurriness exceeds a blurriness threshold.

2. The apparatus of claim 1, wherein the blurriness analyzer is to determine the probability of blurriness by:

applying an edge detection filter to the first photograph;

identifying pixels having a pixel value above a pixel value threshold;

estimating a variance of pixel values corresponding to the identified pixels within a first area of the multiple areas of the first photograph, the variance of the pixel values is a first variance of a plurality of variances of the pixel values, the first variance associated with the first area of the first photograph; and

determining the probability of blurriness based on the estimated variance.

3. The apparatus of claim 2, wherein the blurriness analyzer is to determine the probability of blurriness by applying a logistic model to the plurality of variances of the pixel values corresponding to the multiple areas of the first photograph.

4. The apparatus of claim 1, wherein the blurriness analyzer is to divide the first photograph into the multiple areas.

5. The apparatus of claim 4, wherein the multiple areas within the subset are spaced apart from a central region of the first photograph.

6. The apparatus of claim 4, wherein the multiple areas within the subset are adjacent sides of the first photograph.

7. The apparatus of claim 1, further including, when the probability of blurriness exceeds the blurriness threshold, a communications interface to transmit the new photograph without the first photograph to a data collection facility.

8. A non-transitory computer readable medium comprising instructions that, when executed, cause a mobile device to at least:

capture a first photograph;

determine a probability of blurriness of the first photograph at a time when the first photograph is captured, the probability of blurriness based on an analysis of a subset of multiple areas of the first photograph, the subset excluding a region of the first photograph associated with an auto-focus operation of the mobile device; and

prompt a user, before displaying the first photograph, to capture a new photograph to replace the first photograph when the probability of blurriness exceeds a blurriness threshold.

9. The non-transitory computer readable medium of claim 8, wherein the instructions further cause the mobile device to determine the probability of blurriness by:

applying an edge detection filter to the first photograph;

identifying pixels having a pixel value above a pixel value threshold;

estimating a variance of pixel values corresponding to the identified pixels within a first area of the multiple areas of the first photograph, the variance of the pixel values is a first variance of a plurality of variances of the pixel values, the first variance associated with the first area of the first photograph; and

determining the probability of blurriness based on the estimated variance.

10. The non-transitory computer readable medium of claim 9, wherein the instructions are further to cause the mobile device to determine the probability of blurriness by applying a logistic model to the plurality of variances of the pixel values corresponding to the multiple areas of the first photograph.

11. The non-transitory computer readable medium of claim 8, wherein the instructions are further to cause the mobile device to divide the first photograph into the multiple areas.

12. The non-transitory computer readable medium of claim 11, wherein the multiple areas within the subset are spaced apart from a central region of the first photograph.

13. The non-transitory computer readable medium of claim 11, wherein the multiple areas within the subset are adjacent sides of the first photograph.

14. The non-transitory computer readable medium of claim 8, wherein, when the probability of blurriness exceeds the blurriness threshold, the instructions are further to cause the mobile device to transmit the new photograph to a data collection facility, and not to transmit the first photograph to the data collection facility.

15. A method comprising:

capturing, by executing an instruction with a processor, a first photograph with a mobile device;

determining, by executing an instruction with the processor, a probability of blurriness of the first photograph at a time when the first photograph is captured, the probability of blurriness based on an analysis of a subset of multiple areas of the first photograph, the subset excluding a region of the first photograph associated with an auto-focus operation of the mobile device; and

prompting, by executing an instruction with the processor, a user to capture a new photograph to replace the first photograph when the probability of blurriness exceeds a blurriness threshold, the prompting occurring before the first photograph is displayed to the user.

16. The method of claim 15, wherein the determining of the probability of blurriness includes:

applying an edge detection filter to the first photograph;

identifying pixels having a pixel value above a pixel value threshold;

estimating a variance of pixel values corresponding to the identified pixels within a first area of multiple areas of the first photograph, the variance of the pixel values is a first variance of a plurality of variances of the pixel values, the first variance associated with the first area of the first photograph; and

determining the probability of blurriness based on the estimated variance.

17. The method of claim 16, wherein the determining of the probability of blurriness includes applying a logistic model to the plurality of variances of the pixel values corresponding to the multiple areas of the first photograph.

18. The method of claim 15, further including dividing the first photograph into the multiple areas.

19. The method of claim 18, wherein the multiple areas within the subset are spaced apart from a central region of the first photograph.

20. The method of claim 15, further including, when the probability of blurriness exceeds the blurriness threshold, transmitting the new photograph to a data collection facility without transmitting the first photograph.