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公开(公告)号:US11279279B2
公开(公告)日:2022-03-22
申请号:US16472760
申请日:2017-12-19
Applicant: SRI International , Toyota Motor Corporation
Inventor: Amir Tamrakar , Girish Acharya , Makoto Okabe , John James Byrnes
Abstract: An evaluation engine has two or more modules to assist a driver of a vehicle. A driver drowsiness module analyzes monitored features of the driver to recognize two or more levels of drowsiness of the driver of the vehicle. The driver drowsiness module evaluates drowsiness of the driver based on observed body language and facial analysis of the driver. The driver drowsiness module is configured to analyze live multi-modal sensor inputs from sensors against at least one of i) a trained artificial intelligence model and ii) a rules based model while the driver is driving the vehicle to produce an output comprising a driver drowsiness-level estimation. A driver assistance module provides one or more positive assistance mechanisms to the driver to return the driver to be at or above the designated level of drowsiness.
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公开(公告)号:US20170160813A1
公开(公告)日:2017-06-08
申请号:US15332494
申请日:2016-10-24
Applicant: SRI International
Inventor: Ajay Divakaran , Amir Tamrakar , Girish Acharya , William Mark , Greg Ho , Jihua Huang , David Salter , Edgar Kalns , Michael Wessel , Min Yin , James Carpenter , Brent Mombourquette , Kenneth Nitz , Elizabeth Shriberg , Eric Law , Michael Frandsen , Hyong-Gyun Kim , Cory Albright , Andreas Tsiartas
IPC: G06F3/01 , G06F3/00 , G06F3/16 , G06N99/00 , G10L25/63 , G10L15/22 , G10L15/06 , G10L15/02 , G06K9/00 , G10L15/18
CPC classification number: G06F3/017 , G06F3/0304 , G06F3/167 , G06K9/00221 , G06K9/00335 , G06N3/006 , G06N5/022 , G06N7/005 , G06N20/00 , G10L15/1815 , G10L15/1822 , G10L15/22 , G10L25/63 , G10L2015/228
Abstract: Methods, computing devices, and computer-program products are provided for implementing a virtual personal assistant. In various implementations, a virtual personal assistant can be configured to receive sensory input, including at least two different types of information. The virtual personal assistant can further be configured to determine semantic information from the sensory input, and to identify a context-specific framework. The virtual personal assistant can further be configured to determine a current intent. Determining the current intent can include using the semantic information and the context-specific framework. The virtual personal assistant can further be configured to determine a current input state. Determining the current input state can include using the semantic information and one or more behavioral models. The behavioral models can include one or more interpretations of previously-provided semantic information. The virtual personal assistant can further be configured to determine an action using the current intent and the current input state.
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公开(公告)号:US10198509B2
公开(公告)日:2019-02-05
申请号:US15005795
申请日:2016-01-25
Applicant: SRI INTERNATIONAL
Inventor: Hui Cheng , Harpreet Singh Sawhney , Ajay Divakaran , Qian Yu , Jingen Liu , Amir Tamrakar , Saad Ali , Omar Javed
IPC: G06F17/30
Abstract: A complex video event classification, search and retrieval system can generate a semantic representation of a video or of segments within the video, based on one or more complex events that are depicted in the video, without the need for manual tagging. The system can use the semantic representations to, among other things, provide enhanced video search and retrieval capabilities.
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公开(公告)号:US20220301290A1
公开(公告)日:2022-09-22
申请号:US17654956
申请日:2022-03-15
Applicant: SRI International
Inventor: Jihua Huang , Amir Tamrakar
IPC: G06V10/776 , G06V10/774 , G06T7/64 , G06T7/73 , G06V40/16 , G06V10/75
Abstract: This disclosure describes techniques for improving accuracy of machine learning systems in facial recognition. The techniques include generating, from a training image comprising a plurality of pixels and labeled with a plurality of facial landmarks, one or more facial contour heatmaps, wherein each of the one or more facial contour heatmaps depicts an estimate of a location of one or more facial contours within the training image. Techniques further include training a machine learning model to process the one or more facial contour heatmaps to predict the location of the one or more facial contours within the training image, wherein training the machine learning model comprises applying a loss function to minimize a distance between the predicted location of the one or more facial contours within the training image and corresponding contour data generated from facial landmarks of the plurality of facial landmarks with which the training image is labeled.
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公开(公告)号:US20210129748A1
公开(公告)日:2021-05-06
申请号:US16472760
申请日:2017-12-19
Applicant: SRI International , Toyota Motor Corporation
Inventor: Amir Tamrakar , Girish Acharya , Makoto Okabe , John James Bymes
Abstract: An evaluation engine has two or more modules to assist a driver of a vehicle. A driver drowsiness module analyzes monitored features of the driver to recognize two or more levels of drowsiness of the driver of the vehicle. The driver drowsiness module evaluates drowsiness of the driver based on observed body language and facial analysis of the driver. The driver drowsiness module is configured to analyze live multi-modal sensor inputs from sensors against at least one of i) a trained artificial intelligence model and ii) a rules based model while the driver is driving the vehicle to produce an output comprising a driver drowsiness-level estimation. A driver assistance module provides one or more positive assistance mechanisms to the driver to return the driver to be at or above the designated level of drowsiness.
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公开(公告)号:US10769459B2
公开(公告)日:2020-09-08
申请号:US15751339
申请日:2016-08-30
Applicant: SRI International
Inventor: Amir Tamrakar , Gregory Ho , David Salter , Jihua Huang
Abstract: A method and a system are provided for monitoring driving conditions. The method includes receiving video data comprising video frames from one or more sensors where the video frames may represent an interior or exterior of a vehicle, detecting and recognizing one or more features from the video data where each feature is associated with at least one driving condition, extracting the one or more features from the video data, developing intermediate features by associating and aggregating the extracted features among the extracted features, and developing a semantic meaning for the at least one driving condition by utilizing the intermediate features and the extracted one or more features.
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7.
公开(公告)号:US09244924B2
公开(公告)日:2016-01-26
申请号:US13737607
申请日:2013-01-09
Applicant: SRI INTERNATIONAL
Inventor: Hui Cheng , Harpreet Singh Sawhney , Ajay Divakaran , Qian Yu , Jingen Liu , Amir Tamrakar , Saad Ali , Omar Javed
IPC: G06F17/30
CPC classification number: G06F17/30823 , G06F17/30023 , G06F17/30784 , G06F17/30817
Abstract: A complex video event classification, search and retrieval system can generate a semantic representation of a video or of segments within the video, based on one or more complex events that are depicted in the video, without the need for manual tagging. The system can use the semantic representations to, among other things, provide enhanced video search and retrieval capabilities.
Abstract translation: 复杂的视频事件分类,搜索和检索系统可以基于视频中描绘的一个或多个复杂事件,而不需要手动标记来生成视频中的视频或片段的语义表示。 该系统可以使用语义表示来提供增强的视频搜索和检索功能。
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8.
公开(公告)号:US20140347475A1
公开(公告)日:2014-11-27
申请号:US14286305
申请日:2014-05-23
Applicant: SRI International
Inventor: Ajay Divakaran , Qian Yu , Amir Tamrakar , Harpreet Singh Sawhney , Jiejie Zhu , Omar Javed , Jingen Liu , Hui Cheng , Jayakrishnan Eledath
IPC: G06K9/00
CPC classification number: G06K9/00771
Abstract: A system for object detection and tracking includes technologies to, among other things, detect and track moving objects, such as pedestrians and/or vehicles, in a real-world environment, handle static and dynamic occlusions, and continue tracking moving objects across the fields of view of multiple different cameras.
Abstract translation: 用于物体检测和跟踪的系统包括在现实环境中检测和跟踪诸如行人和/或车辆之类的移动物体的技术,处理静态和动态遮挡,以及继续跟踪所有场中的移动物体 的多个不同的相机的视图。
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公开(公告)号:US12073305B2
公开(公告)日:2024-08-27
申请号:US16085859
申请日:2017-03-17
Applicant: SRI International
Inventor: Mohamed R. Amer , Timothy J. Shields , Amir Tamrakar , Max Ehrlich , Timur Almaev
IPC: G06N3/045 , G06F18/2132 , G06F18/24 , G06N5/04 , G06N20/00
CPC classification number: G06N3/045 , G06F18/2132 , G06F18/24 , G06N5/04 , G06N20/00
Abstract: Technologies for analyzing multi-task multimodal data to detect multi-task multimodal events using a deep multi-task representation learning, are disclosed. A combined model with both generative and discriminative aspects is used to share information during both generative and discriminative processes. The technologies can be used to classify data and also to generate data from classification events. The data can then be used to morph data into a desired classification event.
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公开(公告)号:US10268900B2
公开(公告)日:2019-04-23
申请号:US15905937
申请日:2018-02-27
Applicant: SRI International
Inventor: Ajay Divakaran , Qian Yu , Amir Tamrakar , Harpreet Singh Sawhney , Jiejie Zhu , Omar Javed , Jingen Liu , Hui Cheng , Jayakrishnan Eledath
IPC: G06K9/00
Abstract: A system for object detection and tracking includes technologies to, among other things, detect and track moving objects, such as pedestrians and/or vehicles, in a real-world environment, handle static and dynamic occlusions, and continue tracking moving objects across the fields of view of multiple different cameras.
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