公开(公告)号：US20230366843A1

公开(公告)日：2023-11-16

申请号：US18029642

申请日：2021-09-30

Applicant: IDLETECHS AS

Inventor： Harald Martens ,  Torbjorn Pedersen ,  Andreas Simskar Wulvik

IPC: G01N25/72 ,  G06T7/00

CPC classification number: G01N25/72 ,  G06T7/001 ,  G01J2005/0077

Abstract: The invention provides a method of and system for a method of monitoring an object using thermal video data. The method comprises capturing thermal video images of a scene comprising the object using one or more thermal imaging cameras, and outputting a thermal video data stream to a processing apparatus. In the processing apparatus, the thermal video data stream is processed by performing a multivariate analysis of the thermal video data stream to generate one or more models of the behaviour of the object. The one or more models includes modelling of temporal development of a thermal signature of the object, and modelling of covariation of the thermal signature between different parts or regions of the scene. The processing comprises establishing one or more normal states of the object using observed data from the thermal video data stream and the one or more models, and comparing observed data from the thermal video data stream with the one or more normal states of the object to determine whether the object is a known condition or an unknown condition. An output signal from the processing apparatus if the object is determined to be in an unknown condition.

公开(公告)号：US20200083902A1

公开(公告)日：2020-03-12

申请号：US16469604

申请日：2017-12-13

Applicant: IDLETECHS AS

Inventor： Harald MARTENS ,  Hodjat RAHMATI ,  Jan Otto REBERG

IPC: H03M7/30 ,  G06F16/28 ,  G06F17/17 ,  G06F17/18 ,  G06F17/14

Abstract: Methods and corresponding apparatuses for compressing, monitoring, decompressing or analyzing multidimensional data in a computer system. A sequence of multidimensional input data is received from a data generating process and is processed by using an approximation model to project respective blocks of input data on a subspace. For each block of data, a residual representing the difference between said data block and a reconstruction of the data block from the projection of the data block on said subspace is calculated. The calculated residual is stored in a repository while the projection of the data block is appended to previously stored projections of data blocks in an output buffer. The approximation model may be extended through analysis of the repository of residuals in order to detect significant patterns. If a significant pattern is found, the pattern may be added as an extension to the approximation model. The extension to the model may be stored or transmitted as a transform packet which defines a transformation from an earlier model to the extended model.