# US 2014/0192133 A1 · Content aware selective adjusting of motion estimation

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- Number: US 2014/0192133 A1
- Document ID: US20140192133A1
- Status: Published application
- Kind: A1
- Application number: 13/977,446
- Filed: 2012-03-28
- Published: 2014-07-10
- Earliest claimed: 2012-03-28
- Assignees: Intel Corporation
- Inventors: Kin-Hang Cheung; Ping Liu
- Web page: https://patentgrep.com/patent/US20140192133A1

## CPC

- H04N 19/53: Multi-resolution motion estimation; Hierarchical motion estimation
- H04N 19/54: using feature points or meshes
- H04N 19/543: using regions
- H04N 5/144: {Movement detection (for video coding H04N19/503; analysis of motion in general G06T7/20)}
- H04N 7/141: {between two video terminals, e.g. videophone (telephonic communication systems combined with television receiver for reception of entertainment or information matter H04M11/085)}
- H04N 19/156: Availability of hardware or computational resources, e.g. encoding based on power-saving criteria
- H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION

## Abstract

Systems, apparatus, articles, and methods are described including operations for content aware selective adjusting of motion estimation.

## Claims

### Claim at position 1

1-25. (canceled)

### Claim 26

A computer-implemented method for content aware selective adjusting of motion estimation, comprising:
receiving visual data, wherein the visual data includes video;
determining a amount of motion based at least in part on the received visual data; and
selectively adjusting a motion estimation applied to the received visual data based at least in part on the determined amount of motion.

### Claim 27 (depends on 26)

The method of claim 26, further comprising performing facial detection for at least one of one or more users based at least in part on the received visual data.

### Claim 28 (depends on 26)

The method of claim 26, further comprising:
performing facial detection for at least one of one or more users based at least in part on the received visual data; and
identifying a target user and a background area based at least in part on the performed facial detection,
wherein the determination of the amount of motion comprises determining the amount of motion based on the target user and not the background area.

### Claim 29 (depends on 26)

The method of claim 26, wherein the motion estimation is adjusted between a base level of motion estimation and an enhanced level of motion estimation, and
wherein the base level of motion estimation is associated with a first level of downscaled visual data and the enhanced level of motion estimation is associated with a second level of visual data where the second level of downscaling is greater than the first level of downscaling.

### Claim 30 (depends on 26)

The method of claim 26, wherein the motion estimation is adjusted between a base level of motion estimation and an enhanced level of motion estimation,
wherein the base level of motion estimation is associated with a first level of downscaled visual data and the enhanced level of motion estimation is associated with a second level of visual data where the second level of downscaling is greater than the first level of downscaling, and
wherein the base level of motion estimation comprises hierarchical motion estimation and the enhanced level of motion estimation comprises super hierarchical motion estimation.

### Claim 31 (depends on 26)

The method of claim 26, further comprising:
receiving power supply data, wherein the power supply data includes an indication of a current power source and/or an indication of battery charge level, wherein the indication of the current power source indicates whether the current power source is a battery-type power source or an external power source, and
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an indication that the current power source is an external power source.

### Claim 32 (depends on 26)

The method of claim 26, further comprising:
receiving power supply data, wherein the power supply data includes an indication of a current power source and/or an indication of battery charge level, wherein the indication of the current power source indicates whether the current power source is a battery-type power source or an external power source, and
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the base level of motion estimation in response to an indication that the current power source is a battery-type power source and an indication that the battery charge level is below a charge threshold value.

### Claim 33 (depends on 26)

The method of claim 26, further comprising:
receiving power supply data, wherein the power supply data includes an indication of a current power source and/or an indication of battery charge level, wherein the indication of the current power source indicates whether the current power source is a battery-type power source or an external power source, and
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an indication that the current power source is a battery-type power source, an indication that the battery charge level is above a given threshold value, and an indication that the determined amount of motion is above a motion threshold value.

### Claim 34 (depends on 26)

The method of claim 26, further comprising:
receiving power supply data, wherein the power supply data includes an indication of a current power source and/or an indication of battery charge level, wherein the indication of the current power source indicates whether the current power source is a battery-type power source or an external power source, and
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the base level of motion estimation in response to an indication that the current power source is a battery-type power source, an indication that the battery charge level is above a given threshold value, and an indication that the determined amount of motion is below a motion threshold value.

### Claim 35 (depends on 26)

The method of claim 26, further comprising:
performing facial detection for at least one of one or more users based at least in part on the received visual data; and
identifying a target user based at least in part on the performed facial detection,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an identification of the target user as a child.

### Claim 36 (depends on 26)

The method of claim 26, further comprising:
performing facial detection for at least one of one or more users based at least in part on the received visual data;
identifying a target user and a background area based at least in part on the performed facial detection, wherein the determination of the amount of motion comprises determining the amount of motion based on the target user and not the background area; and
receiving power supply data, wherein the power supply data includes an indication of a current power source and/or an indication of battery charge level, wherein the indication of the current power source indicates whether the current power source is a battery-type power source or an external power source,
wherein the motion estimation is adjusted between a base level of motion estimation and an enhanced level of motion estimation, wherein the base level of motion estimation is associated with a first level of downscaled visual data and the enhanced level of motion estimation is associated with a second level of visual data where the second level of downscaling is greater than the first level of downscaling, and wherein the base level of motion estimation comprises hierarchical motion estimation and the enhanced level of motion estimation comprises super hierarchical motion estimation,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an indication that the current power source is an external power source,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the base level of motion estimation in response to an indication that the current power source is a battery-type power source and an indication that the battery charge level is below a charge threshold value,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an indication that the current power source is a battery-type power source, an indication that the battery charge level is above a given threshold value, and an indication that the determined amount of motion is above a motion threshold value,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the base level of motion estimation in response to an indication that the current power source is a battery-type power source, an indication that the battery charge level is above a given threshold value, and an indication that the determined amount of motion is below a motion threshold value, and
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an identification of the target user as a child.

### Claim 37

A system for content aware selective adjusting of motion estimation on a computer, comprising:
an imaging device configured to capture visual data;
one or more processors communicatively coupled to the imaging device;
one or more memory stores communicatively coupled to the one or more processors;
a visual data logic module communicatively coupled to imaging device and configured to receive visual data, wherein the visual data includes video;
a motion determination logic module communicatively coupled to the visual data logic module and configured to determine a amount of motion based at least in part on the received visual data;
a motion estimation adjustment logic module communicatively coupled to the motion determination logic module and configured to selectively adjust a motion estimation applied to the received visual data based at least in part on the determined amount of motion; and
a video encoder communicatively coupled to the motion estimation adjustment logic module and configured to encode the received video data based at least in part on the selectively adjusted motion estimation.

### Claim 38 (depends on 37)

The system of claim 37, further comprising a facial detection logic module communicatively coupled to the visual data logic module and configured to perform facial detection for at least one of one or more users based at least in part on the received visual data.

### Claim 39 (depends on 37)

The system of claim 37, further comprising:
a facial detection logic module communicatively coupled to the visual data logic module and configured to perform facial detection for at least one of one or more users based at least in part on the received visual data and identify a target user and a background area based at least in part on the performed facial detection, and
wherein the determination of the amount of motion comprises determining the amount of motion based on the target user and not the background area.

### Claim 40 (depends on 37)

The system of claim 37, wherein the motion estimation is adjusted between a base level of motion estimation and an enhanced level of motion estimation, and
wherein the base level of motion estimation is associated with a first level of downscaled visual data and the enhanced level of motion estimation is associated with a second level of visual data where the second level of downscaling is greater than the first level of downscaling.

### Claim 41 (depends on 37)

The system of claim 37, wherein the motion estimation is adjusted between a base level of motion estimation and an enhanced level of motion estimation,
wherein the base level of motion estimation is associated with a first level of downscaled visual data and the enhanced level of motion estimation is associated with a second level of visual data where the second level of downscaling is greater than the first level of downscaling, and
wherein the base level of motion estimation comprises hierarchical motion estimation and the enhanced level of motion estimation comprises super hierarchical motion estimation.

### Claim 42 (depends on 37)

The system of claim 37, further comprising:
a power supply data logic module communicatively coupled to the one or more processors and the one or more memory stores and configured to receive power supply data, wherein the power supply data includes an indication of a current power source and/or an indication of battery charge level, wherein the indication of the current power source indicates whether the current power source is a battery-type power source or an external power source, and
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an indication that the current power source is an external power source.

### Claim 43 (depends on 37)

The system of claim 37, further comprising:
a power supply data logic module communicatively coupled to the one or more processors and the one or more memory stores and configured to receive power supply data, wherein the power supply data includes an indication of a current power source and/or an indication of battery charge level, wherein the indication of the current power source indicates whether the current power source is a battery-type power source or an external power source, and
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the base level of motion estimation in response to an indication that the current power source is a battery-type power source and an indication that the battery charge level is below a charge threshold value.

### Claim 44 (depends on 37)

The system of claim 37, further comprising:
a power supply data logic module communicatively coupled to the one or more processors and the one or more memory stores and configured to receive power supply data, wherein the power supply data includes an indication of a current power source and/or an indication of battery charge level, wherein the indication of the current power source indicates whether the current power source is a battery-type power source or an external power source, and
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an indication that the current power source is a battery-type power source, an indication that the battery charge level is above a given threshold value, and an indication that the determined amount of motion is above a motion threshold value.

### Claim 45 (depends on 37)

The system of claim 37, further comprising:
a power supply data logic module communicatively coupled to the one or more processors and the one or more memory stores and configured to receive power supply data, wherein the power supply data includes an indication of a current power source and/or an indication of battery charge level, wherein the indication of the current power source indicates whether the current power source is a battery-type power source or an external power source, and
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the base level of motion estimation in response to an indication that the current power source is a battery-type power source, an indication that the battery charge level is above a given threshold value, and an indication that the determined amount of motion is below a motion threshold value.

### Claim 46 (depends on 37)

The system of claim 37, wherein the video encoder comprises at least a portion of one or more of the logic modules including the visual data logic module, the motion determination logic module, and the motion estimation adjustment logic module.

### Claim 47 (depends on 37)

The system of claim 37, further comprising:
a facial detection logic module communicatively coupled to the visual data logic module and configured to perform facial detection for at least one of one or more users based at least in part on the received visual data and identify a target user based at least in part on the performed facial detection, and
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an identification of the target user as a child.

### Claim 48 (depends on 37)

The system of claim 37, further comprising:
a facial detection logic module communicatively coupled to the visual data logic module and configured to perform facial detection for at least one of one or more users based at least in part on the received visual data and identify a target user and a background area based at least in part on the performed facial detection, and wherein the determination of the amount of motion comprises determining the amount of motion based on the target user and not the background area; and
a power supply data logic module communicatively coupled to the one or more processors and the one or more memory stores and configured to receive power supply data, wherein the power supply data includes an indication of a current power source and/or an indication of battery charge level, wherein the indication of the current power source indicates whether the current power source is a battery-type power source or an external power source,
wherein the motion estimation is adjusted between a base level of motion estimation and an enhanced level of motion estimation, wherein the base level of motion estimation is associated with a first level of downscaled visual data and the enhanced level of motion estimation is associated with a second level of visual data where the second level of downscaling is greater than the first level of downscaling, and wherein the base level of motion estimation comprises hierarchical motion estimation and the enhanced level of motion estimation comprises super hierarchical motion estimation,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an indication that the current power source is an external power source,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the base level of motion estimation in response to an indication that the current power source is a battery-type power source and an indication that the battery charge level is below a charge threshold value,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an indication that the current power source is a battery-type power source, an indication that the battery charge level is above a given threshold value, and an indication that the determined amount of motion is above a motion threshold value, and
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the base level of motion estimation in response to an indication that the current power source is a battery-type power source, an indication that the battery charge level is above a given threshold value, and an indication that the determined amount of motion is below a motion threshold value,
wherein the video encoder comprises at least a portion of one or more of the logic modules including the visual data logic module, the motion determination logic module, the motion estimation adjustment logic module, the facial detection logic module, and the power supply data logic module,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an identification of the target user as a child.

### Claim 49

At least one machine readable medium comprising a plurality of instructions that in response to being executed on a computing device, cause the computing device to code data by:
receiving visual data, wherein the visual data includes video;
determining a amount of motion based at least in part on the received visual data; and
selectively adjusting a motion estimation applied to the received visual data based at least in part on the determined amount of motion.

### Claim 50 (depends on 49)

The machine readable medium of claim 49, further comprising instructions that in response to being executed on the computing device, cause the computing device to operate by:
performing facial detection for at least one of one or more users based at least in part on the received visual data;
identifying a target user and a background area based at least in part on the performed facial detection, wherein the determination of the amount of motion comprises determining the amount of motion based on the target user and not the background area; and
receiving power supply data, wherein the power supply data includes an indication of a current power source and/or an indication of battery charge level, wherein the indication of the current power source indicates whether the current power source is a battery-type power source or an external power source,
wherein the motion estimation is adjusted between a base level of motion estimation and an enhanced level of motion estimation, wherein the base level of motion estimation is associated with a first level of downscaled visual data and the enhanced level of motion estimation is associated with a second level of visual data where the second level of downscaling is greater than the first level of downscaling, and wherein the base level of motion estimation comprises hierarchical motion estimation and the enhanced level of motion estimation comprises super hierarchical motion estimation,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an indication that the current power source is an external power source,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the base level of motion estimation in response to an indication that the current power source is a battery-type power source and an indication that the battery charge level is below a charge threshold value,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an indication that the current power source is a battery-type power source, an indication that the battery charge level is above a given threshold value, and an indication that the determined amount of motion is above a motion threshold value,
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the base level of motion estimation in response to an indication that the current power source is a battery-type power source, an indication that the battery charge level is above a given threshold value, and an indication that the determined amount of motion is below a motion threshold value, and
wherein the selectively adjusted motion estimation applied to the received visual data comprises selectively adjusting the motion estimation to the enhanced level of motion estimation in response to an identification of the target user as a child.