Portrait image processing method and portrait image processing apparatus

Abstract

A portrait image processing method and a portrait image processing device are disclosed. The portrait image processing method is used in a portrait image processing device and includes: (a) obtaining a BVP (Blood Volume Pulse) signal of a user; (b) obtaining a blood flow distribution of a specific part of the user; (c) capturing an image of the specific part; and (d) adjusting the image of the specific part according to the BVP signal and the blood flow distribution. The present application can adjust the parameters of the portrait image of the user based on the BVP signal, so that the adjusted portrait image is more realistic or more lifelike.

Claims

1. A portrait image processing method, used in a portrait image processing device, characterized in that, include: (a) Obtain the user's BVP (Blood Volume Pulse) signal; (b) Obtain the blood flow distribution of a specific part of the user; the specific part is the user's face; the blood flow distribution includes the facial blood flow distribution of the user's face pre-recorded in a storage device, or, a standard facial blood flow distribution pre-recorded in a storage device. (c) Capture an image of the specific portion; and (d) Adjust the image of the specific portion based on the BVP signal and the blood flow distribution; Step (d) synthesizes the BVP signal into the image of the specific portion based on the blood flow distribution; Step (d) synthesizes the BVP signal into the image of the specific portion based on the response of the BVP signal and the signal response in the R channel, G channel or B channel; Further includes: Display the user interface on the screen; Adjust the synthesis level, which is the level at which the BVP signal is synthesized into the image of that specific part.

2. The portrait image processing method as described in claim 1, characterized in that, Step (d) synthesizes the BVP signal into the image of that specific part using the following formula; Where W is the weight of the BVP signal in the R channel, the G channel, or the B channel, F(x,y) is the blood flow distribution, and BVP(t) is the BVP signal.

3. The portrait image processing method as described in claim 1, characterized in that, Step (a) captures an image of the user's hand or neck, and step (a) obtains the BVP signal based on the image of the hand or the image of the neck.

4. The portrait image processing method as described in claim 1, characterized in that, Step (a) involves sensing the BVP signal via the wearable device worn by the user.

5. A human image processing device, characterized in that, include: A camera used to capture images of specific parts of a user's body; as well as Processing circuitry; The processing circuit is used to handle the following steps: (a) Obtain the user's BVP (Blood Volume Pulse) signal; (b) Obtaining the blood flow distribution of the specific portion; the specific portion being the user's face; the blood flow distribution including a facial blood flow distribution of the user's face pre-recorded in a storage device, or a standard facial blood flow distribution pre-recorded in a storage device; and (c) Adjust the image of the specific portion based on the BVP signal and the blood flow distribution; Step (c) synthesizes the BVP signal onto the image of the specific portion based on the blood flow distribution; Step (c) synthesizes the BVP signal onto the image of the specific portion based on the response of the BVP signal and the signal response in the R channel, G channel or B channel; The device further includes a screen, the processing circuitry controlling the screen to display a user interface for adjusting the synthesis level, the synthesis level being the level at which the BVP signal is synthesized into the image of the specific portion.

6. The portrait image processing apparatus as described in claim 5, characterized in that, Step (c) synthesizes the BVP signal into the image of that specific portion using the following formula; Where W is the weight of the BVP signal in the R channel, the G channel, or the B channel, F(x,y) is the blood flow distribution, and BVP(t) is the BVP signal.

7. The portrait image processing apparatus as described in claim 5, characterized in that, Step (a) captures an image of the user's hand or neck, and step (a) obtains the BVP signal based on the image of the hand or the image of the neck.

8. The portrait image processing apparatus as described in claim 5, characterized in that, Step (a) involves sensing the BVP signal via the wearable device worn by the user.

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