PATENT CLAIM ANALYSIS

Application Number: 16337931
Application Type: Utility
Filing Date: 2019-03
Publication Date: 2019-07
Patent Classification: ["382", "118000"]

Abstract:
The disclosure discloses an action unit (AU) feature recognition method, which includes: acquiring a real-time image shot by a photographic device and extracting a real-time facial image from the real-time image by use of a face recognition algorithm; inputting the real-time facial image into a pretrained facial mean shape and recognizing t facial feature points from the real-time facial image by use of the facial mean shape; determining feature regions matched with each AU in the real-time facial image according to positions of the t facial feature points, extracting local features from the feature regions and generating multiple feature vectors; and inputting the multiple feature vectors into pretrained AU classifiers matched with the feature regions respectively to obtain a prediction result of recognition of the corresponding AU features from the feature regions. The disclosure also discloses an electronic device and a computer-readable storage medium.

Claim (Index 1):
An electronic device, comprising: a memory, a processor and a photographic device, an action unit (AU) feature recognition program being stored in the memory and the AU feature recognition program being executed by the processor to implement the following steps of:\n a real-time image capturing step: acquiring a real-time image shot by the photographic device and extracting a real-time facial image from the real-time image by use of a face recognition algorithm; a facial feature point recognition step: inputting the real-time facial image into a pretrained facial mean shape and recognizing t facial feature points from the real-time facial image by use of the facial mean shape, wherein the training steps for the facial mean shape comprising: establishing a first sample library with n facial images and marking t facial feature points at positions of eyes, eyebrows, noses, mouths and facial outer contours in each of the facial images; and training a facial feature recognition model by use of the t facial feature points to obtain the facial mean shape, where t represents a concatenation sequence number; a local feature extraction step: determining feature regions matched with each AU in the real-time facial image according to positions of the t facial feature points, extracting local features from the feature regions and generating multiple feature vectors; and an AU feature prediction step: inputting the multiple feature vectors into pretrained AU classifiers matched with the feature regions respectively to obtain a prediction result of recognition of the corresponding AU features from the feature regions.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 99.0
- Lexical Diversity: 2.26471
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['16338456', '16338457', '16337934', '11062424', '14019748']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3667196513353301
- 35 USC 102 Novelty (BERT): 0.5241127914195964
- Combined Prediction Score: 0.3824589653437567
- Mean Citation Score: 265.465326
- Max Citation Score: 352.45914
- Similarity Product: 304.1506118089628

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 0

Dataset: test