公开(公告)号：US10185895B1

公开(公告)日：2019-01-22

申请号：US15467546

申请日：2017-03-23

Applicant: GOPRO, INC.

Inventor： Daniel Tse ,  Desmond Chik ,  Guanhang Wu

IPC: G06K9/46 ,  G06K9/34 ,  G06N3/04 ,  G06K9/62 ,  G06K9/00 ,  G06T5/20

Abstract: An image including a visual capture of a scene may be accessed. The image may be processed through a convolutional neural network. The convolutional neural network may generate a set of two-dimensional feature maps based on the image. The set of two-dimensional feature maps may be processed through a contextual long short-term memory unit. The contextual long short-term memory unit may generate a set of two-dimensional outputs based on the set of two-dimensional feature maps. A set of attention-masks for the image may be generated based on the set of two-dimensional outputs and the set of two-dimensional feature maps. The set of attention-masks may define dimensional portions of the image. The scene may be classified based on the two-dimensional outputs.

公开(公告)号：US20200257957A1

公开(公告)日：2020-08-13

申请号：US15435241

申请日：2017-02-16

Applicant: GOPRO, INC.

Inventor： Daniel Tse ,  Guanhang Wu ,  Desmond Chik

IPC: G06N3/04 ,  G06N3/08

Abstract: A set of sensor information conveyed by sensor output signals may be accessed. The sensor output signals may be generated by a set of sensors. The set of sensor information may characterize an event monitored by the set of sensors. A multi-feature convolutional neural network may be trained using a branch-loss function. The branch-loss function may include individual loss functions for individual sensor information and one or more combined loss functions for combined sensor information. The set of sensor information may be processed through the multi-feature convolutional neural network. A classification of the event may be obtained from the multi-feature convolutional network based on the set of sensor information.

公开(公告)号：US10534966B1

公开(公告)日：2020-01-14

申请号：US15422852

申请日：2017-02-02

Applicant: GOPRO, INC.

Inventor： Daniel Tse ,  Desmond Chik ,  Guanhang Wu

IPC: G06K9/00 ,  G01P13/00

Abstract: Systems and method of identifying activities and/or events represented in a video are presented herein. An activity and/or event may be represented in a video by virtue of one or both of an entity moving with a capture device during capture of the video preforming the activity and/or event, or the video portraying one or more entities performing the activity and/or event. Activity types may be characterized by one or more of common movements, equipment, spatial context, and/or other features. Events may be characterized by one or both of individual movements and/or sets of movements that may routinely occur during performance of an activity. The identification of activities and/or events represented in a video may be based on one or more spectrogram representations of sensor output signals of one or more sensors coupled to a capture device.