Rapid auto-focus using classifier chains, MEMS and multiple object focusing

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Quick Facts

Patent No.: US 8,797,448
App. No.: 14/174,821
Filed: Feb 6, 2014
Granted: Aug 5, 2014
Kind: B2
Examiner: TRAN, NHAN T
Art Unit: 2664
USPC: 348/345

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Abstract

A smart-focusing technique includes identifying an object of interest, such as a face, in a digital image. A focus-generic classifier chain is applied that is trained to match both focused and unfocused faces and/or data from a face tracking module is accepted. Multiple focus-specific classifier chains are applied, including a first chain trained to match substantially out of focus faces, and a second chain trained to match slightly out of focus faces. Focus position is rapidly adjusted using a MEMS component.

Claims (87)

1. A method comprising:

acquiring data of a digital image which depicts one or more objects;

determining a plurality of in-focus probabilities by applying a plurality of in-focus classifier sets to the data;

wherein each in-focus probability indicates a likelihood that any of the one or more objects is depicted in focus in the digital image;

determining an in-focus cumulative probability based on the plurality of in-focus probabilities;

determining whether the in-focus cumulative probability is below an in-focus threshold;

in response to determining that the in-focus cumulative probability is below the in-focus threshold, performing the steps of:

determining a plurality of slightly-out-of-focus probabilities by applying a plurality of slightly-out-of-focus classifier sets to the data;

wherein each slightly-out-of-focus probability indicates a likelihood that any of the one or more objects is depicted slightly-out-of focus in the digital image;

determining slightly-out-of-focus cumulative probability based on the plurality of slightly-out-of-focus probabilities; and

in response to determining that the slightly-out-of-focus cumulative probability is equal to, or above, a slightly-out-of-focus threshold, determining a particular object, of the one or more objects, that is depicted in the digital image slightly-out-of-focus; and

wherein the method is performed by one or more computing devices.

2. The method of claim 1 ,

wherein an in-focus classifier set of the plurality of in-focus classifier sets comprises an in-focus-program configured to determine an in-focus probability that any of the one or more objects is depicted in-focus in the digital image;

wherein a slightly-out-of-focus classifier set of the one or more slightly-out-of-focus classifier sets comprises a slightly-out-of-focus-program configured to determine a slightly-out-of-focus probability that any of the one or more objects is depicted slightly-out-of-focus in the digital image; and

wherein the slightly-out-of-focus cumulative probability is computed from one or more slightly-out-of-focus probabilities determined by the one or more slightly-out-of-focus classifier sets.

3. The method of claim 2 , further comprising:

determining whether the slightly-out-of-focus cumulative probability is below a slightly-out-of-focus threshold; and

in response to determining that the slightly-out-of-focus cumulative probability is below, the slightly-out-of-focus threshold, applying one or more significantly-out-of-focus classifier sets to determine a significantly-out-of-focus cumulative probability.

4. The method of claim 3 ,

wherein a significantly-out-of-focus classifier set of the one or more significantly-out-of-focus classifier sets comprises a significantly-out-of-focus-program configured to determine a significantly-out-of-focus probability that any of the one or more objects is depicted significantly-out-of-focus in the digital image; and

wherein the significantly-out-of-focus cumulative probability is computed from one or more significantly-out-of-focus probabilities determined by the one or more significantly-out-of-focus classifier sets.

5. The method of claim 4 , further comprising:

determining whether the significantly-out-of-focus cumulative probability is equal to, or above, a significantly-out-of-focus threshold; and

in response to determining that the significantly-out-of-focus cumulative probability is equal to, or above, a significantly-out-of-focus threshold, determining the particular object, of the one or more objects, that is depicted in the digital image significantly-out-of-focus.

6. The method of claim 5 , further comprising:

determining whether the significantly-out-of-focus cumulative probability is below the significantly-out-of-focus threshold; and

in response to determining that the significantly-out-of-focus cumulative probability is below the significantly-out-of-focus threshold, determining that none of the one or more objects is depicted in the digital image.

7. The method of claim 6 , further comprising:

in response to determining that the in-focus cumulative probability is above, or equal to, the in-focus threshold, determining the particular object, of the one or more objects, that is depicted in-focus face in the digital image.

8. A non-transitory computer-readable storage medium, storing one or more computer instructions which, when executed by one or more processors, cause the one or more processors to perform: