公开(公告)号：US20230206596A1

公开(公告)日：2023-06-29

申请号：US17928500

申请日：2021-06-30

Applicant: Sony Semiconductor Solutions Corporation

Inventor： Hideaki Yamamoto

IPC: G06V10/75 ,  G06V20/40 ,  G06V10/25 ,  G06V20/58 ,  G06V20/62

CPC classification number: G06V10/759 ,  G06V20/46 ,  G06V10/25 ,  G06V20/584 ,  G06V20/625

Abstract: The present technique relates to an information processing device, an information processing method, and a program that can improve tracking performance.
A feature information extracting unit extracts feature information about an object for each frame image, and a tracking unit tracks a vehicle in the frame image by using the feature information. The present technique is applicable to a driving support device with an onboard camera, for example.

公开(公告)号：US11657592B2

公开(公告)日：2023-05-23

申请号：US17304742

申请日：2021-06-24

Applicant: ZHEJIANG DAHUA TECHNOLOGY CO., LTD.

Inventor： Xinyi Ren ,  Feng Wang ,  Haitao Sun ,  Jianping Xiong

IPC: G06V10/44 ,  H04N7/18 ,  G06V20/52 ,  G06V30/413 ,  G06V10/75 ,  G06V10/52

CPC classification number: G06V10/44 ,  G06V10/52 ,  G06V10/759 ,  G06V20/52 ,  G06V30/413 ,  H04N7/183

Abstract: The present disclosure relates to systems and methods for object recognition. The system may obtain an image and a model. The image may include a search region in which the object recognition process is performed. In the objection recognition process, for each of one or more sub-regions of the search region, the system may determine a match metric indicating a similarity between the model and the sub-region of the search region. Further, the system may determine an instance of the model among the one or more sub-regions of the search region based on the match metrics.

公开(公告)号：US12112518B2

公开(公告)日：2024-10-08

申请号：US17768923

申请日：2019-11-08

Applicant: NEC Corporation

Inventor： Katsuhiko Takahashi ,  Yuichi Nakatani ,  Tetsuo Inoshita ,  Asuka Ishii ,  Gaku Nakano

IPC: G06V10/75

CPC classification number: G06V10/759

Abstract: In the object detection device, the plurality of object detection units output a score indicating a probability that a predetermined object exists, for each partial region set with respect to image data inputted. The weight computation unit computes a weight for each of the plurality of object detection units by using weight computation parameters and based on the image data. The weights are used when the scores outputted by the plurality of object detection units are merged. The weight redistribution unit changes the weight for a predetermined object detection unit, among the weights computed by the weight computation unit, to 0 and output the weights. The merging unit merges the scores outputted by the plurality of object detection units for each of the partial regions, by using the weights computed by the weight computation unit and including the weight changed by the weight redistribution unit. The loss computation unit computes a difference between a ground truth label of the image data and the merged score merged by the merging unit as a loss. Then, the parameter correction unit corrects the weight computation parameters so as to reduce the loss.

公开(公告)号：US12094234B2

公开(公告)日：2024-09-17

申请号：US17602969

申请日：2020-03-26

Applicant: Beijing Jingdong Shangke Information Technology Co., Ltd. ,  Beijing Jingdong Century Trading Co., Ltd.

Inventor： Qian Bao ,  Wu Liu ,  Tao Mei

IPC: G06V40/10 ,  G06T7/73 ,  G06V10/20 ,  G06V10/46 ,  G06V10/74 ,  G06V10/75 ,  G06V10/82

CPC classification number: G06V40/10 ,  G06T7/73 ,  G06V10/255 ,  G06V10/46 ,  G06V10/757 ,  G06V10/759 ,  G06V10/761 ,  G06V10/82 ,  G06T2207/20076 ,  G06T2207/20084 ,  G06T2207/30196

Abstract: Embodiments of the present application disclose a method and apparatus for detecting a body. A particular embodiment of the method comprises: acquiring a set of candidate body image region in a target image; for a candidate body image region in the set of candidate body image region: acquiring position information and confidences of candidate body key points in the candidate body image region; determining the candidate body key points within a body contour according to body contour information in the candidate body image region and the acquired position information; and determining a confidence score of the candidate body image region according to a sum of the confidences of the candidate body key points within the body contour; and determining a body image region from the set of candidate body image regions according to the confidence scores of the candidate body image regions in set of the candidate body image regions.

公开(公告)号：US12087041B2

公开(公告)日：2024-09-10

申请号：US18565315

申请日：2022-05-30

Applicant: Carl Zeiss Microscopy GmbH

Inventor： Alexander Freytag ,  Matthias Eibl ,  Christian Kungel ,  Anselm Brachmann ,  Daniel Haase ,  Manuel Amthor

IPC: G06V10/26 ,  G06T5/20 ,  G06T5/70 ,  G06T7/00 ,  G06T11/00 ,  G06V10/75 ,  G06V10/774 ,  G06V10/776 ,  G06V10/82

CPC classification number: G06V10/774 ,  G06T5/20 ,  G06T5/70 ,  G06T7/0002 ,  G06T11/001 ,  G06V10/273 ,  G06V10/759 ,  G06V10/776 ,  G06V10/82 ,  G06T2207/10056 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30024 ,  G06T2207/30168

Abstract: A method generates an image processing model to calculate a virtually stained image from a microscope image. The image processing model is trained using training data comprising microscope images as input data into the image processing model and target images that are formed via chemically stained images registered locally in relation to the microscope images. The image processing model is trained to calculate virtually stained images from the input microscope images by optimizing an objective function that captures a difference between the virtually stained images and the target images. After a number of training steps, at least one weighting mask is defined using one of the chemically stained images and an associated virtually stained image calculated after the number of training steps. In the weighting mask, one or more image regions are weighted based on differences between locally corresponding image regions in the virtually stained image and in the chemically stained image. Subsequent training considers the weighting mask in the objective function.

公开(公告)号：US12080067B2

公开(公告)日：2024-09-03

申请号：US17461755

申请日：2021-08-30

Applicant: Meta Platforms, Inc.

Inventor： Gediminas Bertasius ,  Heng Wang ,  Lorenzo Torresani

IPC: G06V10/50 ,  G06F18/21 ,  G06N3/045 ,  G06N3/08 ,  G06N20/00 ,  G06V10/56 ,  G06V10/75 ,  G06V10/82 ,  G06V20/40

CPC classification number: G06V20/41 ,  G06F18/21 ,  G06N20/00 ,  G06V10/56 ,  G06V10/751 ,  G06V20/48 ,  G06V10/759

Abstract: In one embodiment, a method includes accessing a stream of F video frames, where each of the F video frames includes N patches that are non-overlapping, generating an initial embedding vector for each of the N×F patches in the F video frames, generating a classification embedding by processing the generated N×F initial embedding vectors using a self-attention-based machine-learning model that computes a temporal attention and a spatial attention for each of the N×F patches, and determining a class of the stream of video frames based on the generated classification embedding.

公开(公告)号：US12073943B2

公开(公告)日：2024-08-27

申请号：US17132086

申请日：2020-12-23

Applicant: Coreline Soft Co., Ltd. ,  THE ASAN FOUNDATION ,  UNIV. OF ULSAN FOUNDATION FOR INDUSTRY COOPERATION

Inventor： Donghoon Yu ,  Jaeyoun Yi ,  Byeong Soo Kim ,  Joon Beom Seo ,  Namkug Kim ,  Sang Min Lee

IPC: G16H50/20 ,  A61B5/08 ,  G06F18/22 ,  G06T7/00 ,  G06T7/11 ,  G06V10/75 ,  G16H30/20 ,  G16H30/40

CPC classification number: G16H50/20 ,  A61B5/08 ,  G06F18/22 ,  G06T7/0012 ,  G06T7/11 ,  G06V10/75 ,  G16H30/20 ,  G16H30/40 ,  G06T2207/30061 ,  G06V10/759

Abstract: Disclosed herein is a computing system for performing medical image analysis. A computing system for performing medical image analysis according to an embodiment of the present invention includes at least one processor. The at least one processor performs image processing on a first medical image, and segments at least one anatomical region in the first medical image. The at least one processor generates a first quantitative parameter for the at least one anatomical region based on quantitative measurement conditions that can be measured in the first medical image, and stores the first quantitative parameter in a database in association with the first medical image and the at least one anatomical region.

公开(公告)号：US20240282073A1

公开(公告)日：2024-08-22

申请号：US18611047

申请日：2024-03-20

Applicant: Aurora Flight Sciences Corporation, a subsidiary of The Boeing Company

Inventor： Benjamin Jafek ,  Samvruta Tumuluru

IPC: G06V10/20 ,  G06F18/20 ,  G06V10/75 ,  G06V20/64

CPC classification number: G06V10/255 ,  G06F18/295 ,  G06V10/751 ,  G06V20/64 ,  G06V10/759

Abstract: A method includes receiving a first image that is captured at a first time. The method also includes detecting a location of a first object in the first image. The method also includes determining a region of interest based at least partially upon the location of the first object in the first image. The method also includes receiving a second image that is captured at a second time. The method also includes identifying the region of interest in the second image. The method also includes detecting a location of a second object in a portion of the second image that is outside of the region of interest.

公开(公告)号：US12020472B2

公开(公告)日：2024-06-25

申请号：US17388386

申请日：2021-07-29

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Xueyi Zou ,  Yiren Zhou ,  Songcen Xu ,  Jianzhuang Liu ,  Youliang Yan

IPC: G06V10/771 ,  G06F18/22 ,  G06T7/246 ,  G06V10/44 ,  G06V10/74 ,  G06V10/75 ,  G11B27/031

CPC classification number: G06V10/771 ,  G06F18/22 ,  G06T7/248 ,  G06V10/44 ,  G06V10/759 ,  G06V10/761 ,  G11B27/031 ,  G06T2207/10016 ,  G06T2207/30242 ,  G06V2201/07

Abstract: An image processing method. The method includes: An electronic device obtains N images, where the N images have a same quantity of pixels and a same pixel location arrangement, and N is an integer greater than 1; the electronic device obtains, based on feature values of pixels located at a same location in the N images, a reference value of the corresponding location; the electronic device determines a target pixel of each location based on a reference value of the location; and the electronic device generates a target image based on the target pixel of each location.

公开(公告)号：US20240185605A1

公开(公告)日：2024-06-06

申请号：US18061565

申请日：2022-12-05

Applicant: Mitsubishi Electric Research Laboratories, Inc.

Inventor： Michael Jones ,  Ashish Singh ,  Erik Learned-Miller

IPC: G06V20/40 ,  G06V10/62 ,  G06V10/74 ,  G06V10/75 ,  G06V10/82 ,  G06V20/52

CPC classification number: G06V20/44 ,  G06V10/62 ,  G06V10/759 ,  G06V10/761 ,  G06V10/82 ,  G06V20/41 ,  G06V20/48 ,  G06V20/49 ,  G06V20/52

Abstract: Embodiments of the present disclosure disclose a method and a system for video anomaly detection. The system is configured to collect a sequence of input video frames of an input video of a scene. In addition, the system is configured to partition each input video frame of the sequence of input video frames into a plurality of input video patches. Further, the system is configured to process each of the plurality of input video patches with one or more classifiers. Each of the one or more classifiers corresponds to a deep neural network trained to estimate one or more attributes of the plurality of input video patches from an output of a penultimate layer of the deep neural network. Furthermore, the system is configured to compare the output of the penultimate layer. The system is further configured to detect an anomaly based on the output of the penultimate layer.