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1. 发明授权

US11778223B2 Method, device, and medium for generating super-resolution video 有权
公开(公告)号：US11778223B2
公开(公告)日：2023-10-03
申请号：US17406845
申请日：2021-08-19
申请人： Wentao Liu , Yuanhao Yu , Yang Wang , Juwei Lu , Xiaolin Wu , Jin Tang
发明人： Wentao Liu , Yuanhao Yu , Yang Wang , Juwei Lu , Xiaolin Wu , Jin Tang
IPC分类号： H04N19/59 , H04N19/51 , H04N19/184 , H04N19/136
CPC分类号： H04N19/51 , H04N19/136 , H04N19/184
摘要： A method, device and computer-readable medium for generating a super-resolution version of a compressed video stream. By leveraging the motion information and residual information in compressed video streams, described examples are able to skip the time-consuming motion-estimation step for most frames and make the most use of the SR results of key frames. A key frame SR module generates SR versions of I-frames and other key frames of a compressed video stream using techniques similar to existing multi-frame approaches to VSR. A non-key frame SR module generates SR version of the non-key inter frames between these key frames by making use of motion information and residual information used to encode the inter frames in the compressed video stream.

2. 发明授权

US11810329B2 Method, system, and device for color measurement of a surface 有权
公开(公告)号：US11810329B2
公开(公告)日：2023-11-07
申请号：US16953029
申请日：2020-11-19
申请人： Yuanhao Yu , Shuhao Li , Juwei Lu , Jin Tang
发明人： Yuanhao Yu , Shuhao Li , Juwei Lu , Jin Tang
IPC分类号： G06T7/90 , G06N3/084 , G06T7/521 , G06T7/557
CPC分类号： G06T7/90 , G06N3/084 , G06T7/521 , G06T7/557
摘要： Methods and systems for determining a surface color of a target surface under an environment with an environmental light source. A plurality of images of the target surface are captured as the target surface is illuminated with a variable intensity, constant color light source and a constant intensity, constant color environmental light source, wherein the intensity of the light source on the target surface is varied by a known amount between the capturing of the images. A color feature tensor, independent of the environmental light source, is extracted from the image data, and used to infer a surface color of the target surface.

3. 发明授权

US11430138B2 Systems and methods for multi-frame video frame interpolation 有权
公开(公告)号：US11430138B2
公开(公告)日：2022-08-30
申请号：US17102114
申请日：2020-11-23
申请人： Zhixiang Chi , Rasoul Mohammadi Nasiri , Zheng Liu , Jin Tang , Juwei Lu
发明人： Zhixiang Chi , Rasoul Mohammadi Nasiri , Zheng Liu , Jin Tang , Juwei Lu
IPC分类号： G06T7/246 , G06N3/08
摘要： Systems and methods for multi-frame video frame interpolation. Higher-order motion modeling, such as cubic motion modeling, achieves predictions of intermediate optical flow between multiple interpolated frames, assisted by relaxation of the constraints imposed by the loss function used in initial optical flow estimation. A temporal pyramidal optical flow refinement module performs coarse-to-fine refinement of the optical flow maps used to generate the intermediate frames, focusing a proportionally greater amount of refinement attention to the optical flow maps for the high-error middle frames. A temporal pyramidal pixel refinement module performs coarse-to-fine refinement of the generated intermediate frames, focusing a proportionally greater amount of refinement attention to the high-error middle frames. A generative adversarial network (GAN) module calculates a loss function for training the neural networks used in the optical flow estimation module, temporal pyramidal optical flow refinement module, and/or temporal pyramidal pixel refinement module.

4. 发明授权

US11669743B2 Adaptive action recognizer for video 有权
公开(公告)号：US11669743B2
公开(公告)日：2023-06-06
申请号：US16874478
申请日：2020-05-14
申请人： Niamul Quader , Juwei Lu , Peng Dai , Wei Li
发明人： Niamul Quader , Juwei Lu , Peng Dai , Wei Li
IPC分类号： H04N21/462 , G06K9/62 , H04N21/466 , G06N3/08 , G06V20/40 , G06N3/04 , H04N21/4402 , G06F9/50
CPC分类号： H04N21/4621 , G06F9/5055 , G06K9/6277 , G06N3/0454 , G06N3/08 , G06V20/41 , H04N21/440227 , H04N21/4666 , G06V20/44
摘要： An adaptive action recognizer for video that performs multiscale spatiotemporal decomposition of video to generate lower complexity video. The adaptive action recognizer has a number of processing pathways, one for each level of video complexity with each processing pathway having a different computational cost. The adaptive action recognizer applies a decision making scheme that encourages using low average computational costs while retaining high accuracy.

5. 发明授权

US11023710B2 Semi-supervised hybrid clustering/classification system 有权
公开(公告)号：US11023710B2
公开(公告)日：2021-06-01
申请号：US16280760
申请日：2019-02-20
申请人： Peng Dai , Juwei Lu , Bharath Sekar , Wei Li , Jianpeng Xu , Ruiwen Li
发明人： Peng Dai , Juwei Lu , Bharath Sekar , Wei Li , Jianpeng Xu , Ruiwen Li
IPC分类号： G06K9/00 , G06K9/62 , G06N20/00 , G06F16/75
摘要： System and method for classifying data objects occurring in an unstructured dataset, comprising: extracting feature vectors from the unstructured dataset, each feature vector representing an occurrence of a data object in the unstructured dataset; classifying the feature vectors into feature vector sets that each correspond to a respective object class from a plurality of object classes; for each feature vector set: performing multiple iterations of a clustering operation, each iteration including clustering feature vectors from the feature vector set into clusters of similar feature vectors and identifying outlier feature vectors, wherein for at least one iteration after a first iteration of the clustering operation, outlier feature vectors identified in a previous iteration are excluded from the clustering operation; and outputting a key cluster for the feature vector set from a final iteration of the multiple iterations, the key cluster including a greater number of similar feature vectors than any of the other clusters of the final iteration; and assembling a dataset that includes at least the feature vectors from the key clusters of the feature vector sets.

6. 发明申请

US20200265218A1 SEMI-SUPERVISED HYBRID CLUSTERING/CLASSIFICATION SYSTEM 审中-公开
公开(公告)号：US20200265218A1
公开(公告)日：2020-08-20
申请号：US16280760
申请日：2019-02-20
申请人： Peng Dai , Juwei Lu , Bharath Sekar , Wei Li , Jianpeng Xu , Ruiwen Li
发明人： Peng Dai , Juwei Lu , Bharath Sekar , Wei Li , Jianpeng Xu , Ruiwen Li
IPC分类号： G06K9/00 , G06K9/62 , G06F16/75 , G06N20/00
摘要： System and method for classifying data objects occurring in an unstructured dataset, comprising: extracting feature vectors from the unstructured dataset, each feature vector representing an occurrence of a data object in the unstructured dataset; classifying the feature vectors into feature vector sets that each correspond to a respective object class from a plurality of object classes; for each feature vector set: performing multiple iterations of a clustering operation, each iteration including clustering feature vectors from the feature vector set into clusters of similar feature vectors and identifying outlier feature vectors, wherein for at least one iteration after a first iteration of the clustering operation, outlier feature vectors identified in a previous iteration are excluded from the clustering operation; and outputting a key cluster for the feature vector set from a final iteration of the multiple iterations, the key cluster including a greater number of similar feature vectors than any of the other clusters of the final iteration; and assembling a dataset that includes at least the feature vectors from the key clusters of the feature vector sets.

7. 发明授权

US07844085B2 Pairwise feature learning with boosting for use in face detection 有权
标题翻译：配对功能学习与增强用于面部检测
公开(公告)号：US07844085B2
公开(公告)日：2010-11-30
申请号：US11759460
申请日：2007-06-07
申请人： Juwei Lu , Hui Zhou
发明人： Juwei Lu , Hui Zhou
IPC分类号： G06K9/00
CPC分类号： G06K9/00228 , G06K9/6257
摘要： Systems and methods for training an AdaBoost based classifier for detecting symmetric objects, such as human faces, in a digital image. In one example embodiment, such a method includes first selecting a sub-window of a digital image. Next, the AdaBoost based classifier extracts multiple sets of two symmetric scalar features from the sub-window, one being in the right half side and one being in the left half side of the sub-window. Then, the AdaBoost based classifier minimizes the joint error of the two symmetric features for each set of two symmetric scalar features. Next, the AdaBoost based classifier selects one of the features from the set of two symmetric scalar features for each set of two symmetric scalar features. Finally, the AdaBoost based classifier linearly combines multiple weak classifiers, each of which corresponds to one of the selected features, into a stronger classifier.
摘要翻译：用于训练基于AdaBoost的分类器的系统和方法，用于在数字图像中检测对象对象（例如人脸）。在一个示例实施例中，这种方法包括首先选择数字图像的子窗口。接下来，基于AdaBoost的分类器从子窗口中提取多组两个对称标量特征，一组位于子窗口的右半边，一个位于子窗口的左半边。然后，基于AdaBoost的分类器最小化两组对称标量特征的两个对称特征的联合误差。接下来，基于AdaBoost的分类器从两组对称标量特征中选择两个对称标量特征集合中的一个特征。最后，基于AdaBoost的分类器将多个弱分类器线性组合，每个弱分类器对应于所选特征之一，成为更强的分类器。

8. 发明授权

US07840037B2 Adaptive scanning for performance enhancement in image detection systems 有权
标题翻译：自适应扫描图像检测系统中的性能增强
公开(公告)号：US07840037B2
公开(公告)日：2010-11-23
申请号：US11684478
申请日：2007-03-09
申请人： Juwei Lu , Hui Zhou , Mohanaraj Thiyagarajah
发明人： Juwei Lu , Hui Zhou , Mohanaraj Thiyagarajah
IPC分类号： G06K9/00 , G06K9/48 , G06K9/68 , G06K9/70
CPC分类号： G06K9/00234 , G06K9/00248
摘要： A method and system for efficiently detecting faces within a digital image. One example method includes identifying a digital image comprised of a plurality of sub-windows and performing a first scan of the digital image using a coarse detection level to eliminate the sub-windows that have a low likelihood of representing a face. The subset of the sub-windows that were not eliminated during the first scan are then scanned a second time using a fine detection level having a higher accuracy level than the coarse detection level used during the first scan to identify sub-windows having a high likelihood of representing a face.
摘要翻译：一种用于有效检测数字图像内的面部的方法和系统。一个示例性方法包括识别由多个子窗口组成的数字图像，并使用粗略检测水平执行数字图像的第一次扫描，以消除具有低的表示脸部可能性的子窗口。然后使用具有比在第一次扫描期间使用的粗略检测级别更高的精度水平的精细检测级别来第二次扫描在第一次扫描期间未被消除的子窗口的子集，以识别具有高似然性的子窗口代表一个脸。

9. 发明授权

US11900260B2 Methods, devices and media providing an integrated teacher-student system 有权
公开(公告)号：US11900260B2
公开(公告)日：2024-02-13
申请号：US16810524
申请日：2020-03-05
申请人： Deepak Sridhar , Juwei Lu
发明人： Deepak Sridhar , Juwei Lu
IPC分类号： G06N3/08 , G06N3/088 , G06N3/045
CPC分类号： G06N3/088 , G06N3/045 , G06N3/08
摘要： Methods, devices and processor-readable media for an integrated teacher-student machine learning system. One or more teacher-student modules are trained as part of the teacher neural network training. Each student sub-network uses a portion of the teacher neural network to generate an intermediate feature map, then provides the intermediate feature map to a student sub-network to generate inferences. The student sub-network may use a feature enhancement block to map the intermediate feature map to a subsequent feature map. A compression block may be used to compress intermediate feature map data for transmission in some embodiments.

10. 发明授权

US11474614B2 Method and device for adjusting the control-display gain of a gesture controlled electronic device 有权
公开(公告)号：US11474614B2
公开(公告)日：2022-10-18
申请号：US17085866
申请日：2020-10-30
申请人： Wei Li , Wei Zhou , Sachi Mizobuchi , Ghazaleh Saniee-Monfared , Juwei Lu , Taslim Arefin Khan , Rafael Veras Guimaraes
发明人： Wei Li , Wei Zhou , Sachi Mizobuchi , Ghazaleh Saniee-Monfared , Juwei Lu , Taslim Arefin Khan , Rafael Veras Guimaraes
IPC分类号： G06F3/01 , G06T7/70 , G06T7/20 , G06T7/50 , G06V40/20 , G06V10/25
摘要： Methods, devices, and processor-readable media for adjusting the control-display gain of a gesture-controlled device are described. Adjusting the control-display gain may facilitate user interaction with content or UI elements rendered on a display screen of the gesture-controlled device. The control-display gain may be adjusted based on a property of how a mid-air dragging gesture is being performed by a user's hand. The property may be the location of the gesture, the orientation of the hand performing the gesture, or the velocity of the gesture. A hand that becomes stationary for a threshold time period while performing the dragging gesture may adjust the control-display gain to a different level. Control-display gain may be set to a different value based on the current velocity of the hand performing the gesture. The control-display gain levels may be selected from a continuous range of values or a set of discrete values. Devices for performing the methods are described.

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