Systems and methods for sizing objects via a computing device

• US 10,755,431 B2
• Filed: 01/13/2020
• Issued: 08/25/2020
• Est. Priority Date: 07/19/2018
• Status: Active Grant

• Current Assignee: Radius Technologies, LLC
• Original Assignee: Radius Technologies, LLC
• Inventors: Shea, John David, Dantin, Jr., Thomas Maurice
• Primary Examiner(s): Park, Soo Jin
• Application Number:
  US16/741,365
• Publication Number:
  US 20200151896A1
• Time in Patent Office: 225 Days
• Field of Search: None
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 30/0623 Item investigation
• CPC Class Codes: G06T 2207/20081 Training; Learning
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/50 Depth or shape recovery
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes
• CPC Class Codes: G06T 7/62 of area, perimeter, diameter or volume

Abstract

The present disclosure generally relates to the measurement of objects. Using unique processes, the present systems and methods can determine the size of an object using a computing device. For example, in certain embodiments, the present systems and methods receive a physical object such as a foot determine the size of the foot in millimeters, and convert the size of the foot in millimeters into a shoe size.

Claims

1. A method for automatically sizing a physical object via an electronic computing device, comprising the steps of:

receiving an indication that the physical object is within a field of view of a sensor of the electronic computing device;

detecting that a bottom surface of the physical object is substantially parallel to the sensor of the electronic computing device;

identifying, via the sensor, a depth of the physical object from the sensor of the electronic computing device, wherein the depth of the physical object from the sensor is determined according to an average depth of the bottom surface of the physical object;

determining, via the electronic computing device, an image of the physical object, wherein the image has an outline defining an outer boundary of the physical object;

determining from the outer boundary of the physical object, a first end and a second end of the physical object;

retrieving a pixel ratio corresponding to the electronic computing device;

determining a pixel length between the first end and the second end of the physical object; and

based on the depth, the pixel ratio, and the pixel length, calculating a physical length of the physical object.

2. The method of claim 1, wherein the sensor of the electronic computing device comprises an infrared sensor.

3. The method of claim 1, further comprising the step of prior to receiving the indication that the physical object is within the field of view of the sensor of the electronic computing device, detecting that the electronic computing device is substantially aligned with a horizontal surface.

4. The method of claim 1, wherein the step of determining the image of the physical object further comprises using image recognition via machine learning based on stored images of prior objects.

5. The method of claim 1, wherein the step of determining the image of the physical object further comprises the steps of:

identifying a pixel depth for each pixel associated with the field of view of the sensor;

identifying a smallest pixel depth;

identifying a subset of pixels in the field of view that are within a predefined threshold measure of the smallest pixel depth; and

defining the subset of pixels as the image of the physical object.

6. The method of claim 1, further comprising the step of prior to determining the pixel length between the first end and the second end of the physical object, determining an angle of inclination of the physical object with respect to a longitudinal axis of the electronic computing device.

7. The method of claim 6, wherein the step of determining the pixel length between the first end and the second end further comprises using a trigonometric function to calculate the pixel length based on the angle of inclination.

8. The method of claim 1, wherein the physical object comprises a human foot.

9. The method of claim 8, wherein the physical length of the human foot is compared to a shoe size chart to identify a shoe size of a user associated with the human foot.

10. A system for automatically sizing a physical object, comprising:

a database configured to store pixel ratios for electronic computing devices; and

an electronic computing device in operative communication with the database, the electronic computing device having a processor operative to;

receive an indication that the physical object is within a field of view of a sensor of the electronic computing device;

detect that a bottom surface of the physical object is substantially parallel to the sensor of the electronic computing device;

identify, via the sensor, a depth of the physical object from the sensor of the electronic computing device, wherein the depth of the physical object from the sensor is determined according to an average depth of the bottom surface of the physical object;

determine an image of the physical object, wherein the image has an outline defining an outer boundary of the physical object;

determine from the outer boundary of the physical object a first end and a second end of the physical object;

retrieve a pixel ratio corresponding to the electronic computing device from the database;

determine a pixel length between the first end and the second end of the physical object; and

based on the depth, the pixel ratio, and the pixel length, calculate a physical length of the physical object.

11. The system of claim 10, wherein the sensor of the electronic computing device comprises an infrared sensor.

12. The system of claim 10, wherein the processor is further operative to, prior to receiving the indication that the physical object is within the field of view of the sensor of the electronic computing device, detect that the electronic computing device is substantially aligned with a horizontal surface.

13. The system of claim 10, wherein determining the image of the physical object further comprises using image recognition via machine learning based on stored images of prior objects.

14. The system of claim 10, wherein the processor is further operative to, with respect to determining the image of the physical object:

identify a pixel depth for each pixel associated with the field of view of the sensor;

identify a smallest pixel depth;

identify a subset of pixels in the field of view that are within a predefined threshold measure of the smallest pixel depth; and

define the subset of pixels as the image of the physical object.

15. The system of claim 10, wherein the processor is further operative to, prior to determining the pixel length between the first end and the second end of the physical object, determine an angle of inclination of the physical object with respect to a longitudinal axis of the electronic computing device.

16. The system of claim 15, wherein determining the pixel length between the first end and the second end further comprises using a trigonometric function to calculate the pixel length based on the angle of inclination.

17. The system of claim 10, wherein the physical object comprises a human foot.

18. The system of claim 17, wherein the physical length of the human foot is compared to a shoe size chart to identify a shoe size of a user associated with the human foot.

19. A method for automatically sizing a physical object via an electronic computing device, comprising the steps of:

receiving an indication that the physical object is within a field of view of a sensor of the electronic computing device;

identifying, via the sensor, a depth of the physical object from the sensor of the electronic computing device;

determining, via the electronic computing device, an image of the physical object, wherein the image has an outline defining an outer boundary of the physical object, and wherein determining the image of the physical object comprises the steps of;

identifying a pixel depth for each pixel associated with the field of view of the sensor;

identifying a smallest pixel depth;

identifying a subset of pixels in the field of view that are within a predefined threshold measure of the smallest pixel depth; and

defining the subset of pixels as the image of the physical object;

determining from the outer boundary of the physical object, a first end and a second end of the physical object;

retrieving a pixel ratio corresponding to the electronic computing device;

determining a pixel length between the first end and the second end of the physical object; and

based on the depth, the pixel ratio, and the pixel length, calculating a physical length of the physical object.

20. The method of claim 19, wherein the sensor of the electronic computing device comprises an infrared sensor.

21. The method of claim 19, further comprising the step of prior to receiving the indication that the physical object is within the field of view of the sensor of the electronic computing device, detecting that the electronic computing device is substantially aligned with a horizontal surface.

22. The method of claim 19, further comprising the step of prior to identifying the depth of the physical object from the sensor, detecting that a bottom surface of the physical object is substantially parallel to the sensor of the electronic computing device.

23. The method of claim 22, wherein the depth of the physical object from the sensor is determined according to an average depth of the bottom surface of the physical object.

24. The method of claim 19, wherein the step of determining the image of the physical object further comprises using image recognition via machine learning based on stored images of prior objects.

25. The method of claim 19, further comprising the step of prior to determining the pixel length between the first end and the second end of the physical object, determining an angle of inclination of the physical object with respect to a longitudinal axis of the electronic computing device.

26. The method of claim 25, wherein the step of determining the pixel length between the first end and the second end further comprises using a trigonometric function to calculate the pixel length based on the angle of inclination.

27. The method of claim 19, wherein the physical object comprises a human foot.

28. The method of claim 27, wherein the physical length of the human foot is compared to a shoe size chart to identify a shoe size of a user associated with the human foot.

29. A system for automatically sizing a physical object, comprising:

a database configured to store pixel ratios for electronic computing devices; and

an electronic computing device in operative communication with the database, the electronic computing device having a processor operative to;

receive an indication that the physical object is within a field of view of a sensor of the electronic computing device;

identify, via the sensor, a depth of the physical object from the sensor of the electronic computing device;

determine an image of the physical object, wherein the image has an outline defining an outer boundary of the physical object, and wherein the processor is further operative to;

identify a pixel depth for each pixel associated with the field of view of the sensor;

identify a smallest pixel depth;

identify a subset of pixels in the field of view that are within a predefined threshold measure of the smallest pixel depth; and

define the subset of pixels as the image of the physical object;

determine from the outer boundary of the physical object a first end and a second end of the physical object;

retrieve a pixel ratio corresponding to the electronic computing device from the database;

determine a pixel length between the first end and the second end of the physical object; and

based on the depth, the pixel ratio, and the pixel length, calculate a physical length of the physical object.

30. The system of claim 29, wherein the sensor of the electronic computing device comprises an infrared sensor.

31. The system of claim 29, wherein the processor is further operative to, prior to receiving the indication that the physical object is within the field of view of the sensor of the electronic computing device, detect that the electronic computing device is substantially aligned with a horizontal surface.

32. The system of claim 29, wherein the processor is further operative to, prior to identifying the depth of the physical object from the sensor, detect that a bottom surface of the physical object is substantially parallel to the sensor of the electronic computing device.

33. The system of claim 32, wherein the depth of the physical object from the sensor is determined according to an average depth of the bottom surface of the physical object.

34. The system of claim 29, wherein determining the image of the physical object further comprises using image recognition via machine learning based on stored images of prior objects.

35. The system of claim 29, wherein the processor is further operative to, prior to determining the pixel length between the first end and the second end of the physical object, determine an angle of inclination of the physical object with respect to a longitudinal axis of the electronic computing device.

36. The system of claim 35, wherein determining the pixel length between the first end and the second end further comprises using a trigonometric function to calculate the pixel length based on the angle of inclination.

37. The system of claim 29, wherein the physical object comprises a human foot.

38. The system of claim 37, wherein the physical length of the human foot is compared to a shoe size chart to identify a shoe size of a user associated with the human foot.