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US 9,361,510 B2Granted
Efficient facial landmark tracking using online shape regression method
AssigneeIntel Corporation
InventorsAnbang Yao, Yangzhou Du, Xiaofeng Tong, Tao Wang, Yurong Chen, Jianguo Li, Jianbo Ye, Wenlong Li, Yimin Zhang
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Abstract
Disclosed in some examples are various modifications to the shape regression technique for use in real-time applications, and methods, systems, and machine readable mediums which utilize the resulting facial landmark tracking methods.
Claims22
A method for detection of facial landmark points, the method comprising:
- detecting a facial image in a first video frame using a face classifier;
- normalizing the detected facial image by applying a first transform to the detected facial image;
- detecting a set of facial landmark points of the normalized facial image using a trained shape regressor;
- computing a set of final facial landmark points in the first video frame by applying a second transform to the facial landmark points, the second transform an inverse transform of the first transform;
- calculating a facial bounding box for a second video frame using the computed set of final facial landmark points from the first video frame;
- normalizing a second facial image in the second video frame by applying a third transform to the second facial image, the second facial image comprising the image of the second video frame within the facial bounding box;
- detecting a second set of facial landmark points in the normalized second facial image using the trained shape regressor;
- and
- computing a second set of final facial landmark points in the second video frame by applying a fourth transform to the facial landmark points, the fourth transform an inverse transform of the third transform.
6 more elements
A device for detection of facial landmark points, the device comprising:
- one or more processors arranged to execute at least:
- a facial classifier module to:
- detect a facial image in a first video frame;
- and
- an online shape regression module to:
- normalize the detected facial image by applying a first transform to the detected facial image;
- detect a set of facial landmark points of the normalized facial image using a trained shape regressor;
- compute a set of final facial landmark points in the first video frame by applying a second transform to the facial landmark points, the second transform a reverse transform of the first transform;
- calculate a facial bounding box for a second video frame using the computed set of final facial landmark points from the first video frame;
- normalize a second facial image in the second video frame by applying a third transform to the second facial image, the second facial image comprising the image of the second video frame within the facial bounding box;
- detect a second set of facial landmark points in the normalized second facial image using the trained shape regressor;
- and
- compute a second set of final facial landmark points in the second video frame by applying a fourth transform to the facial landmark points, the fourth transform an inverse transform of the third transform.
10 more elements
A non-transitory machine readable medium for detection of facial landmark points, the machine readable medium storing instructions, which when performed by a machine, cause the machine to perform operations comprising:
- detecting a facial image in a first video frame using a face classifier;
- normalizing the detected facial image by applying a first transform to the detected facial image;
- detecting a set of facial landmark points of the normalized facial image using a trained shape regressor;
- and
- computing a set of final facial landmark points in the first video frame by applying a second transform to the facial landmark points, the second transform an inverse transform of the first transform;
- calculating a facial bounding box for a second video frame using the computed set of final facial landmark points from the first video frame;
- normalizing a second facial image in the second video frame by applying a third transform to the second facial image, the second facial image comprising the image of the second video frame within the facial bounding box;
- detecting a second set of facial landmark points in the normalized second facial image using the trained shape regressor;
- and
- computing a second set of final facial landmark points in the second video frame by applying a fourth transform to the facial landmark points, the fourth transform an inverse transform of the third transform.
7 more elements
Dependencies are inferred from the claim text.