公开(公告)号：US20240338421A1

公开(公告)日：2024-10-10

申请号：US18748918

申请日：2024-06-20

Applicant: Intuitive Surgical Operations, Inc.

Inventor： Brian D. Hoffman ,  Geoffrey A. Richmond ,  Siddarth Sen

IPC: G06F18/20 ,  G06F18/21 ,  G06F18/214 ,  G06F18/24 ,  G06N3/04 ,  G06V10/82

CPC classification number: G06F18/285 ,  G06F18/214 ,  G06F18/2163 ,  G06F18/24 ,  G06N3/04 ,  G06V10/82 ,  G06V2201/031

Abstract: An imaging system is provided for pixel-level segmentation of images comprising: a camera to capture images of an anatomical object and to represent the images in two-dimensional (2D) arrangements of pixels; one or more processors and a non-transitory computer readable medium with information including: CNN instructions to cause the one or more processors to implement a CNN configured to associate anatomical object classifications with pixels of the 2D arrangements of pixels; and multiple sets of weights, to differently configure the CNN based upon different camera image training data; and a display screen configured to display the two-dimensional (2D) arrangements of classified pixels and the anatomical object classifications.

公开(公告)号：US20240338084A1

公开(公告)日：2024-10-10

申请号：US18440605

申请日：2024-02-13

Applicant: GOOGLE LLC

Inventor： Dongeek Shin ,  Andrea Colaco ,  Stiven Guillaume Francois Morvan ,  Adam James Banfield ,  Shahram Izadi

IPC: G06F3/01 ,  G06F1/16 ,  G06V10/82 ,  G06V20/20 ,  G06V40/10 ,  G06V40/13 ,  G06V40/20

CPC classification number: G06F3/017 ,  G06F1/163 ,  G06V10/82 ,  G06V20/20 ,  G06V40/1318 ,  G06V40/15 ,  G06V40/28

Abstract: Techniques of operating an AR system include determining hand gestures formed by a user based on a sequence of two-dimensional images through skin of the user's wrist acquired from a near-infrared camera. Specifically, an image capture device disposed on a band worn around a user's wrist includes a source of electromagnetic radiation, e.g., light-emitting diodes in the infrared (IR) wavelength band that emit the radiation into the user's wrist and an IR detector which produces the sequence of two-dimensional images of a region within a dermal layer in the user's wrist. From this sequence, gesture detection circuitry determines values of a biological flow metric, e.g., a change in perfusion index (PI) between frames of the sequence, based on a trained model that generates the metric from the sequence. Finally, the gesture detection circuitry maps the values of the biological flow metric to specific hand/finger movements that determine a gesture.

公开(公告)号：US20240337535A1

公开(公告)日：2024-10-10

申请号：US18749966

申请日：2024-06-21

Applicant: Changchun Institute Of Optics, Fine Mechanics And Physics, Chinese Academy Of Sciences

Inventor： DONG YAO ,  HANGANG LIANG ,  CHUNMING JIANG

IPC: G01J3/447 ,  G01J3/28 ,  G06T5/70 ,  G06V10/764 ,  G06V10/82 ,  G06V20/10

CPC classification number: G01J3/447 ,  G01J3/2823 ,  G06T5/70 ,  G06V10/764 ,  G06V10/82 ,  G06V20/10

Abstract: A polarization intelligent sensing system and a polarization intelligent sensing method are provided. The polarization intelligent sensing method includes performing the polarization imaging on the target scene to obtain the polarization image, performing the calculation on the polarization image to obtain the polarization information of the target scene, generating the image information to be restored of the target scene according to the polarization information of the target scene, and constructing the multi-dimensional target detection neural network based on the DETR, and obtaining the interpretation information of the target scene based on the image information to be restored of the target scene, the spectral information, or the intensity information through the neural networks. The system and the method are widely applied to environments of various carrying platforms, has strong environmental adaptability, and is capable of obtaining target scene information that cannot be sensed by a conventional optical sensor.

公开(公告)号：US20240335110A1

公开(公告)日：2024-10-10

申请号：US18574471

申请日：2022-06-27

Applicant: INIVATION AG

Inventor： Thomas DEBRUNNER ,  Pierre GIRAUD

IPC: A61B3/113 ,  A61B3/15 ,  G06F3/01 ,  G06V10/82 ,  G06V40/19

CPC classification number: A61B3/113 ,  A61B3/152 ,  G06F3/013 ,  G06V10/82 ,  G06V40/19

Abstract: An eye tracking device that includes: an event-based optical sensor configured to receive radiation reflected off an eye of a user and produce a signal stream of events, each event corresponding to detection of a temporal change in the received radiation at pixels of the sensor; glint sources configured to send radiation to the eye that is reflected off the cornea and received by the sensor in the form of individual glints; a controller connected to the sensor and configured to receive the signal stream from the sensor and to generate: gaze information of the eye and first glint information of the glints, at a first instant of time; and second glint information of the glints at a second instant of time that is later than the first instant of time. The controller is configured to generate predicted gaze information at the second instant of time.

公开(公告)号：US12114022B2

公开(公告)日：2024-10-08

申请号：US17285509

申请日：2018-10-17

Applicant: Telefonaktiebolaget LM Ericsson (publ)

Inventor： Volodya Grancharov ,  Manish Sonal

IPC: G06T7/136 ,  G06F18/21 ,  G06F18/22 ,  G06V10/44 ,  G06V10/54 ,  G06V10/56 ,  G06V10/764 ,  G06V10/82 ,  G06V10/98 ,  G06V20/20 ,  G06V20/40 ,  G06V20/56 ,  H04N19/89

CPC classification number: H04N19/89 ,  G06F18/2193 ,  G06F18/22 ,  G06T7/136 ,  G06V10/454 ,  G06V10/54 ,  G06V10/56 ,  G06V10/764 ,  G06V10/82 ,  G06V10/993 ,  G06V20/20 ,  G06V20/40 ,  G06V20/56 ,  G06T2207/10016

Abstract: There is provided mechanisms for identifying decreasing object detectability for a video stream. A method is performed by a controller. The method includes receiving the video stream over a communication channel. The method includes receiving first visual object detection (VOD) data of the video stream. The first VOD data has been obtained from the video stream before is sent over the communication channel towards the controller. The method includes obtaining second VOD data of the video stream. The second VOD data is obtained from the video stream after is received by the controller. The method includes determining, by comparing the first VOD data to the second VOD data, whether any object present in the first VOD data has a decreased object detectability in the second VOD data, thereby identifying the decreasing object detectability for the video stream. The method includes issuing a notification when the decreasing object detectability has been identified.

公开(公告)号：US12112553B2

公开(公告)日：2024-10-08

申请号：US18314747

申请日：2023-05-09

Applicant: Hayden AI Technologies, Inc.

Inventor： Vaibhav Ghadiok ,  Christopher Carson ,  Bo Shen

IPC: G06K9/00 ,  G06N3/08 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82 ,  G06V20/56 ,  G06V20/58

CPC classification number: G06V20/588 ,  G06N3/08 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82 ,  G06V20/58 ,  G06V2201/08

Abstract: Disclosed herein are systems, methods, and devices for detecting traffic lane violations. In one embodiment, a method for detecting a potential traffic violation is disclosed comprising bounding a vehicle detected from one or more video frames of a video in a vehicle bounding box. The vehicle can be detected and bounded using a first convolutional neural network. The method can also comprise bounding, using the one or more processors of the edge device, a plurality of lanes of a roadway detected from the one or more video frames in a plurality of polygons. The plurality of lanes can be detected and bounded using multiple heads of a multi-headed second convolutional neural network. The method can further comprise detecting a potential traffic violation based in part on an overlap of at least part of the vehicle bounding box and at least part of one of the polygons.

公开(公告)号：US12112536B1

公开(公告)日：2024-10-08

申请号：US18401066

申请日：2023-12-29

Applicant: Tartan Aerial Sense Tech Private Limited

Inventor： Dhivakar Kanagaraj ,  Pranav M P ,  Raghul Raghu ,  Prakash Mathews Pothen

IPC: G06V20/10 ,  G06T5/40 ,  G06T5/70 ,  G06T7/11 ,  G06T7/136 ,  G06V10/26 ,  G06V10/77 ,  G06V10/774 ,  G06V10/82

CPC classification number: G06V20/188 ,  G06T5/40 ,  G06T5/70 ,  G06T7/11 ,  G06T7/136 ,  G06V10/273 ,  G06V10/7715 ,  G06V10/7747 ,  G06V10/82 ,  G06T2207/10024 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30188

Abstract: A camera apparatus includes control circuitry, where in a training phase, the control circuitry is configured to generate a set of binary images of foliage masks, where each binary image comprises one or more foliage regions demarcated from a non-foliage region. A modified training dataset of color images is generated and a custom neural network model for foliage detection is trained. The control circuitry causes the custom neural network model to not only learn a plurality of features related to foliage but also learn a color variation range of predefined color associated with the plurality of features and utilize combination of the plurality of features related to foliage and the color variation range to obtain trained custom neural network model. The control circuitry is configured to operate the trained custom neural network model to detect one or more foliage regions in a new color image in real time.

公开(公告)号：US12112529B2

公开(公告)日：2024-10-08

申请号：US17230455

申请日：2021-04-14

Applicant: HYUNDAI MOTOR COMPANY ,  KIA CORPORATION

Inventor： Min Woo Kang ,  Soon Woo Kwon ,  Chung An Lee ,  Hyun Ki Kim ,  Seung Hyun Hong ,  Jun Yun Kang

IPC: G06V10/82 ,  G06F18/2132 ,  G06F18/24 ,  G06N3/044 ,  G06N3/045 ,  G06N3/048 ,  G06N3/08 ,  G06N3/082 ,  G06N20/00 ,  G06T3/60 ,  G06T7/00 ,  G06T7/11 ,  G06V20/70

CPC classification number: G06V10/82 ,  G06F18/2132 ,  G06F18/24 ,  G06N3/044 ,  G06N3/045 ,  G06N3/08 ,  G06N3/082 ,  G06T3/60 ,  G06T7/0002 ,  G06T7/0004 ,  G06T7/11 ,  G06V20/70 ,  G06N3/048 ,  G06N20/00 ,  G06T2207/10056 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30136 ,  G06T2207/30168

Abstract: An apparatus and a method for segmenting a steel microstructure phase are provided. The apparatus includes a storage configured for storing a machine learning algorithm and a processing device that segments a microstructure phase using the machine learning algorithm. The processing device is configured to receive label data, to learn a machine learning model by use of the label data as learning data for the machine learning model, and to segment a phase of a steel microstructure image by use of the learned machine learning model.

公开(公告)号：US12112527B2

公开(公告)日：2024-10-08

申请号：US17564512

申请日：2021-12-29

Applicant: HON HAI PRECISION INDUSTRY CO., LTD.

Inventor： Tung-Tso Tsai ,  Chin-Pin Kuo ,  Tzu-Chen Lin ,  Shih-Chao Chien

IPC: G06V10/778 ,  G06N3/04 ,  G06T7/00 ,  G06V10/774 ,  G06V10/82 ,  G06V10/94

CPC classification number: G06V10/7796 ,  G06N3/04 ,  G06T7/0002 ,  G06V10/774 ,  G06V10/82 ,  G06V10/95 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30168

Abstract: In a method for defecting surface defects, a trained weighting generated when defect-free training samples are used to train an autoencoder and pixel convolutional neural network is obtained. A test encoding feature is obtained by inputting the trained weighting into the autoencoder and pixel convolutional neural network and a weighted autoencoder of the weighted autoencoder and pixel convolutional neural network encoding a test sample. The test encoding feature is input into a weighted pixel convolution neural network of the weighted autoencoder and pixel convolutional neural network to output a result of test. The test result is either no defect in the test sample or at least one defect in the test sample. Inaccurate determinations as to defects are thereby avoided. An electronic device and a non-transitory storage medium are also disclosed.

公开(公告)号：US12112512B1

公开(公告)日：2024-10-08

申请号：US17835726

申请日：2022-06-08

Applicant: Blue Yonder Group, Inc.

Inventor： Mayank Tiwari ,  Ankit Belchandan ,  Bharani Sarvepalli ,  Santosh Kumar

IPC: G06V10/22 ,  G06T7/60 ,  G06T15/20 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06V10/235 ,  G06T7/60 ,  G06T15/205 ,  G06V10/764 ,  G06V10/82

Abstract: A system and method are disclosed for virtual planogram automation with computer vision, comprising a retail entity comprising a product display area; and a planogram planner configured to access images of products prior to the display of the products in the product display area, classify the images by using a convolutional neural network, assign a bounding box to the products identified in the images, localize and detect objects and estimate product dimensions corresponding to the objects, determine changes in the estimated product dimensions by comparing the estimated product dimensions with corresponding baseline product dimensions to determine whether product dimensions has changed, and determine a total area remaining in a simulated planogram for alternative product placements after factoring in the determined changes in product dimensions.