公开(公告)号：US10147200B2

公开(公告)日：2018-12-04

申请号：US15464927

申请日：2017-03-21

Applicant: Axis AB

Inventor： Hanna Bjorgvinsdottir ,  Jiandan Chen

IPC: G06K9/00 ,  G06T7/73 ,  G06N3/04 ,  G06N3/08 ,  G06K9/62 ,  G06T11/60

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for classifying an object occurring in a sequence of images. The object is tracked through the sequence of images. A set of temporally distributed image crops including the object is generated from the sequence of images. The set of image crops is fed to an artificial neural network trained for classifying an object. The artificial network determines a classification result for each image crop. A quality measure of each classification result is determined based on one or more of: a confidence measure of a classification vector output from the artificial neural network, and a resolution of the image crop. The classification result for each image crop is weighed by its quality measure, and an object class for the object is determined by combining the weighted output from the artificial neural network for the set of images.

公开(公告)号：US20180276845A1

公开(公告)日：2018-09-27

申请号：US15464927

申请日：2017-03-21

Applicant: Axis AB

Inventor： Hanna Bjorgvinsdottir ,  Jiandan Chen

IPC: G06T7/73 ,  G06N3/04 ,  G06N3/08 ,  G06K9/62

CPC classification number: G06T7/73 ,  G06K9/6265 ,  G06K9/6267 ,  G06K9/6292 ,  G06N3/04 ,  G06N3/084 ,  G06T11/60 ,  G06T2207/20084 ,  G06T2210/22

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for classifying an object occurring in a sequence of images. The object is tracked through the sequence of images. A set of temporally distributed image crops including the object is generated from the sequence of images. The set of image crops is fed to an artificial neural network trained for classifying an object. The artificial network determines a classification result for each image crop. A quality measure of each classification result is determined based on one or more of: a confidence measure of a classification vector output from the artificial neural network, and a resolution of the image crop. The classification result for each image crop is weighed by its quality measure, and an object class for the object is determined by combining the weighted output from the artificial neural network for the set of images.