Face searching and detection in a digital image acquisition device
AssigneeFotoNation Limited
InventorsEran STEINBERG, Petronel BIGIOI, Peter CORCORAN, Mihnea GANGEA, Stefan PETRESCU, Andrei VASILIU, Gabriel COSTACHE, Alexandru DRIMBAREAN
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Abstract
A method of detecting a face in an image includes performing face detection within a first window of the image at a first location. A confidence level is obtained from the face detection indicating a probability of the image including a face at or in the vicinity of the first location. Face detection is then performed within a second window at a second location, wherein the second location is determined based on the confidence level.
Claims9
-20. (canceled)
A method comprising:
- acquiring data of a digital image which depicts one or more objects;
- determining a first size of a first detection window and an initial location of the first detection window in the digital image;
- wherein the first detection window encompasses a first portion of the digital image;
- determining, for the first detection window, first detection window data that represents the first detection window at a first image resolution level;
- determining a first set of face detection tests that are to be applied to the first detection window data;
- applying the first set of face detection tests to the first detection window data to determine a first confidence level value that indicates a likelihood that a particular object, of the one or more objects, is included in the first detection window;
- in response to determining that the first confidence level value is not greater than a first threshold value:
- determining a second size that is greater than the first size;
- determining a second detection window that has the second size;
- wherein the second detection window encompasses a second portion of the digital image;
- determining, for the second detection window, second detection window data that represents the second detection window at a second image resolution level;
- determining a second set of face detection tests that are to be applied to the second detection window data;
- and applying the second set of face detection tests to the second detection window data to determine a second confidence level value that indicates a likelihood that the particular object, of the one or more objects, is included in the second detection window;
- and wherein the method is performed using one or more computing devices.
A non-transitory computer-readable storage medium, storing one or more instructions which, when executed by one or more processors, cause the one or more processors to perform:
- acquiring data of a digital image which depicts one or more objects;
- determining a first size of a first detection window and an initial location of the first detection window in the digital image;
- wherein the first detection window encompasses a first portion of the digital image;
- determining, for the first detection window, first detection window data that represents the first detection window at a first image resolution level;
- determining a first set of face detection tests that are to be applied to the first detection window data;
- applying the first set of face detection tests to the first detection window data to determine a first confidence level value that indicates a likelihood that a particular object, of the one or more objects, is included in the first detection window;
- in response to determining that the first confidence level value is not greater than a first threshold value:
- determining a second size that is greater than the first size;
- determining a second detection window that has the second size;
- wherein the second detection window encompasses a second portion of the digital image;
- determining, for the second detection window, second detection window data that represents the second detection window at a second image resolution level;
- determining a second set of face detection tests that are to be applied to the second detection window data;
- and applying the second set of face detection tests to the second detection window data to determine a second confidence level value that indicates a likelihood that the particular object, of the one or more objects, is included in the second detection window.
Dependencies are inferred from the claim text.