1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.
10 years of news and resources for members of the IEEE Signal Processing Society
For our May 2015 issue, we cover recent patents granted in the area of visual gait recognition. The section below covers patents granted recently for gait recognition technologies in computer generated reality, visual behavior recognition, access management and motion classification.
In patent no. 8,966,400 Technologies are generally described for a system for interpreting user movement in computer generated reality. In some examples, the system includes a user interface effective to generate movement data relating to movement of the user interface. In some examples, the system further includes a processor receive the movement data. In some examples, the processor is further effective to define a coordinate system based on the movement data and map the movement data to the coordinate system to produce mapped movement data. In some examples, the processor is further effective to determine a feature of the mapped movement data and to map the feature to a code. In some examples, the processor is further effective to send the code to the application and receive application data from the application in response to the code. In some examples, the processor is further effective to generate an image based on the application data.
A system for analyzing gait using textile sensors is disclosed in patent no. 8,961,439. A system includes a sock sensing system, which comprises a sock and at least one switch, tension sensor, or pressure sensor for sensing a posture or movement; and a processor configured to receive signals from the sock sensing system and to analyze a gait parameter, wherein the processor is configured to calculate the gait parameter using a signal from the sock sensing system as a trigger point.
In patent 8,948,499 a system is described for object and behavior recognition which utilizes a collection of modules which, when integrated, can automatically recognize, learn, and adapt to simple and complex visual behaviors. An object recognition module utilizes a cooperative swarm algorithm to classify an object in a domain. A graph-based object representation module is configured to use a graphical model to represent a spatial organization of the object within the domain. Additionally, a reasoning and recognition engine module consists of two sub-modules: a knowledge sub-module and a behavior recognition sub-module. The knowledge sub-module utilizes a Bayesian network, while the behavior recognition sub-module consists of layers of adaptive resonance theory clustering networks and a layer of a sustained temporal order recurrent temporal order network. The described invention has applications in video forensics, data mining, and intelligent video archiving.
Embodiments of the invention no. 8,860,549 provide a method, system and computer program product for managing an opening through gait recognition. The method includes capturing imagery, for example through the use of a Web cam, of a moving object as the moving object approaches an automated door. The method additionally, includes determining from the captured imagery a presence or absence of a gait of the moving object. Finally, the method includes managing an automated opening of the door according to the determined presence or absence of a gait of the moving object.
A motion classification system proposed by patent no. 8,548,740 comprises an inertial measurement unit configured to sense motion of a user and to output one or more channels of inertial motion data corresponding to the sensed motion; and a processing unit configured to calculate a coefficient vector for each of the one or more channels based on a wavelet transformation of the respective inertial motion data, and to select one of a plurality of gaits as the user's gait based on the calculated coefficient vector of at least one of the one or more channels and on a plurality of templates, each template corresponding to one of the plurality of gaits.
If you have an interesting patent to share when we next feature patents related to gait recognition techniques, or if you are especially interested in a signal processing research field that you would want to be highlighted in this section, please send email to Csaba Benedek (benedek.csaba AT sztaki DOT mta DOT hu).
Title: User movement interpretation in computer generated reality
Inventors: Y. Tralvex
Issued: February 24, 2015
Assignee: Empire Technology Development LLC (Wilmington, DE)
Title: System and method for analyzing gait using fabric sensors
Inventors: C-M. Yang, T-L. Yang, C-W Yang and H Yang
Issued: February 24, 2015
Assignee: Ming Young Biomedical Corp. (Miaoli, TW)
Title: Method for online learning and recognition of visual behaviors
Inventors: S. Medasani, D.L. Allen, S.E. Chelian and Y. Owechko
Issued: February 3, 2015
Assignee: HRL Laboratories, LLC (Malibu, CA)
Title: System and method for wavelet-based gait classification
Inventors: J. Hesch, Y. Ma and P. Lommel
Issued: October 1, 2013
Assignee: Honeywell International Inc. (Morristown, NJ)
© Copyright 2020 IEEE – All rights reserved. Use of this website signifies your agreement to the IEEE Terms and Conditions.
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.