Techniques for determining proximity based on image blurriness

Patent metadata

Field	Value
Publication number	US-2018018024-A1
Application number	US-201615208417-A
Country	US
Kind code	A1
Filing date	Jul 12, 2016
Priority date	Jul 12, 2016
Publication date	Jan 18, 2018
Grant date	—

Abstract

Certain aspects of the present disclosure generally relate to determining proximity based on image blurriness. In some aspects, a device may analyze an image sensed by an image sensor of the device. The device may determine a metric based on analyzing the image. The metric may provide an indication of a blurriness or a sharpness of the image. The device may determine, based on the metric, a measure of proximity associated with the image.

First claim

1 . A method, comprising:
analyzing, by a device, an image sensed by an image sensor of the device; determining, by the device, a metric indicative of a blurriness or a sharpness of the image sensed by the image sensor based on analyzing the image; determining, by the device and based on the metric indicative of the blurriness or the sharpness of the image sensed by the image sensor, a measure of proximity associated with the image,
different measures of proximity corresponding to different values of the metric indicative of the blurriness or the sharpness of the image sensed by the image sensor; and
controlling, by the device, a power property of a display based on the measure of proximity.

2 . (canceled)

3 . The method of claim 1 , wherein analyzing the image comprises:
analyzing the image based on at least one of:
a local binary pattern, or
a local ternary pattern.

4 . The method of claim 1 , wherein determining the metric comprises:
determining the metric based on one or more computer vision features detected in the image.

5 . The method of claim 1 , further comprising:
masking a portion of the image; and determining the metric based on masking the portion of the image.

6 . The method of claim 5 , further comprising:
receiving input associated with masking the image; and masking the portion of the image based on the input.

7 . The method of claim 1 , further comprising:
determining that accelerometer data, generated by an accelerometer of the device, satisfies a threshold; and analyzing the image based on determining that the accelerometer data satisfies the threshold.

8 . The method of claim 1 , further comprising:
segmenting the image into a plurality of blocks; determining respective metrics for multiple blocks of the plurality of blocks; and determining the metric based on the respective metrics.

9 . The method of claim 1 , wherein the device includes at least one of:
a mobile device, or an occupancy sensor.

10 . A device, comprising:
one or more processors to:
analyze an image sensed by an image sensor of the device;
determine a metric indicative of a blurriness or a sharpness of the image sensed by the image sensor based on analyzing the image;
determine, based on the metric indicative of the blurriness or the sharpness of the image sensed by the image sensor, a measure of proximity associated with the image,
different measures of proximity corresponding to different values of the metric indicative of the blurriness or the sharpness of the image sensed by the image sensor; and

control a power property of a display based on the measure of proximity.

11 . (canceled)

12 . The device of claim 10 , wherein the one or more processors, when analyzing the image, are to:
analyze the image based on at least one of:
a local binary pattern, or
a local ternary pattern.

13 . The device of claim 10 , wherein the one or more processors, when determining the metric, are to:
determine the metric based on one or more computer vision features detected in the image.

14 . The device of claim 10 , wherein the one or more processors are further to:
mask a portion of the image; and determine the metric based on masking the portion of the image.

15 . The device of claim 14 , wherein the one or more processors are further to:
receive input associated with masking the image; and mask the portion of the image based on the input.

16 . The device of claim 10 , wherein the one or more processors are further to:
determine that accelerometer data, generated by an accelerometer of the device, satisfies a threshold; and analyze the image based on determining that the accelerometer data satisfies the threshold.

17 . A non-transitory computer-readable medium storing instructions, the instructions comprising:
one or more instructions that, when executed by one or more processors of a device, cause the one or more processors to:
analyze an image sensed by an image sensor of the device;
determine a metric indicative of a blurriness or a sharpness of the image sensed by the image sensor based on analyzing the image;
determine, based on the metric indicative of the blurriness or the sharpness of the image sensed by the image sensor, a measure of proximity associated with the image,
different measures of proximity corresponding to different values of the metric indicative of the blurriness or the sharpness of the image sensed by the image sensor; and

control a power property of a display based on the measure of proximity.

18 . (canceled)

19 . The non-transitory computer-readable medium of claim 17 , wherein the one or more instructions, that cause the one or more processors to analyze the image, cause the one or more processors to:
analyze the image based on at least one of:
a local binary pattern, or
a local ternary pattern.

20 . The non-transitory computer-readable medium of claim 17 , wherein the one or more instructions, that cause the one or more processors to determine the metric, cause the one or more processors to:
determine the metric based on one or more computer vision features detected in the image.

21 . The non-transitory computer-readable medium of claim 17 , wherein the one or more instructions, when executed by the one or more processors, cause the one or more processors to:
mask a portion of the image; and determine the metric based on masking the portion of the image.

22 . The non-transitory computer-readable medium of claim 17 , wherein the one or more instructions, when executed by the one or more processors, cause the one or more processors to:
determine that accelerometer data, generated by an accelerometer of the device, satisfies a threshold; and analyze the image based on determining that the accelerometer data satisfies the threshold.

23 . The non-transitory computer-readable medium of claim 17 , wherein the one or more instructions, when executed by the one or more processors, cause the one or more processors to:
segment the image into a plurality of blocks; determine respective metrics for multiple blocks of the plurality of blocks; and determine the metric based on the respective metrics.

24 . An apparatus, comprising:
means for analyzing an image sensed by an image sensor of the apparatus; means for determining a metric indicative of a blurriness or a sharpness of the image sensed by the image sensor based on analyzing the image; means for determining, based on the metric indicative of the blurriness or the sharpness of the image sensed by the image sensor, a measure of proximity associated with the image,
different measures of proximity corresponding to different values of the metric indicative of the blurriness or the sharpness of the image sensed by the image sensor; and
means for controlling a power property of a display based on the measure of proximity.

25 . (canceled)

26 . The apparatus of claim 24 , wherein the means for analyzing the image comprises:
means for analyzing the image based on at least one of:
a local binary pattern,
a local ternary pattern, or
an analysis of a plurality of segments included in the image.

27 . The apparatus of claim 24 , wherein the means for determining the metric comprises:
means for determining the metric based on one or more computer vision features detected in the image.

Assignees

• Qualcomm Inc

Inventors

• Park Edwin Chongwoo

Classifications

• G06T7/60

  Analysis of geometric attributes · CPC title

• G06F3/0304 Primary

  Detection arrangements using opto-electronic means (constructional details of pointing devices not related to the detection arrangement using opto-electronic means G06F3/033; optical digitisers G06F3/042) · CPC title

• G06F3/0346

  with detection of the device orientation or free movement in a three-dimensional [3D] space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors · CPC title

• G06T7/0002

  Inspection of images, e.g. flaw detection · CPC title

• G06T7/529 Primary

  from texture · CPC title