Adaptive pattern recognition based control system and method

• US 10,361,802 B1
• Filed: 02/02/2000
• Issued: 07/23/2019
• Est. Priority Date: 02/01/1999
• Status: Expired due to Fees

• Current Assignee: Hoffberg Family Trust 2, Blanding Hovenweep LLC (Intellectual Ventures LLC), STEVEN M. HOFFBERG 2004-1 GRAT
• Original Assignee: Blanding Hovenweep LLC (Intellectual Ventures LLC)
• Inventors: Hoffberg-Borghesani, Linda I., Hoffberg, Steven M.
• Primary Examiner(s): Salce, Jason P
• Application Number:
  US94/970,71
• Time in Patent Office: 7,111 Days
• Field of Search: 725 44- 47, 725 34- 36, 725 52- 59, 725 37- 39
• CPC Class Codes: G06F 3/00 Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
• CPC Class Codes: G06F 3/048 Interaction techniques based on graphical user interfaces [GUI]
• CPC Class Codes: G06F 9/453 Help systems
• CPC Class Codes: G06V 40/103 Static body considered as a whole, e.g. static pedestrian or occupant recognition
• CPC Class Codes: G11B 27/107 of operating tapes
• CPC Class Codes: G11B 27/11 by using information not detectable on the record carrier
• CPC Class Codes: G11B 27/328 on a tape [TTOC]
• CPC Class Codes: H04B 1/205 with control bus for exchanging commands between units
• CPC Class Codes: H04H 60/33 Arrangements for monitoring the users' behaviour or opinions
• CPC Class Codes: H04H 60/46 for recognising users' preferences
• CPC Class Codes: H04H 60/65 for using the result on users' side
• CPC Class Codes: H04N 2005/91307 by adding a copy protection signal to the video signal
• CPC Class Codes: H04N 2005/91328 the copy protection signal being a copy management signal, e.g. a copy generation management signal [CGMS]
• CPC Class Codes: H04N 2005/91364 the video signal being scrambled
• CPC Class Codes: H04N 21/4147 PVR [Personal Video Recorder] H04N5/76 takes precedence ; arrangements for broadcast with accumulation-type receivers H04H20/40
• CPC Class Codes: H04N 21/42201 biosensors, e.g. heat sensor for presence detection, EEG sensors or any limb activity sensors worn by the user input arrangements for interaction with the human body based on nervous system activity detection G06F3/015
• CPC Class Codes: H04N 21/4334 Recording operations recording of a television signal H04N5/76; arrangements for recording or accumulating broadcast information or broadcast-related information H04H60/27
• CPC Class Codes: H04N 21/44008 involving operations for analysing video streams, e.g. detecting features or characteristics in the video stream arrangements characterised by components specially adapted for monitoring, identification or recognition of video in broadcast systems H04H60/59
• CPC Class Codes: H04N 21/44224 Monitoring of user activity on external systems, e.g. Internet browsing
• CPC Class Codes: H04N 21/4532 involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/454 : Content or additional data filtering, e.g. blocking advertisements
• CPC Class Codes: H04N 21/4583 : Automatically resolving scheduling conflicts, e.g. when a recording by reservation has been programmed for two programs in the same time slot
• CPC Class Codes: H04N 21/466 : Learning process for intelligent management, e.g. learning user preferences for recommending movies services using the results of monitoring in broadcast systems H04H60/61
• CPC Class Codes: H04N 21/4666 : using neural networks, e.g. processing the feedback provided by the user
• CPC Class Codes: H04N 21/4667 : Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections
• CPC Class Codes: H04N 21/4668 : for recommending content, e.g. movies
• CPC Class Codes: H04N 21/4755 : for defining user preferences, e.g. favourite actors or genre retrieval personalisation and generation of user profiles for the retrieval of video data G06F16/739; user profiles in network data switching protocols H04L67/306
• CPC Class Codes: H04N 5/782 : on tape
• CPC Class Codes: H04N 5/913 : for scrambling ; for copy protection

Abstract

An adaptive interface for a programmable system, for predicting a desired user function, based on user history, as well as machine internal status and context. The apparatus receives an input from the user and other data. A predicted input is presented for confirmation by the user, and the predictive mechanism is updated based on this feedback. Also provided is a pattern recognition system for a multimedia device, wherein a user input is matched to a video stream on a conceptual basis, allowing inexact programming of a multimedia device. The system analyzes a data stream for correspondence with a data pattern for processing and storage. The data stream is subjected to adaptive pattern recognition to extract features of interest to provide a highly compressed representation that may be efficiently processed to determine correspondence. Applications of the interface and system include a video cassette recorder (VCR), medical device, vehicle control system, audio device, environmental control system, securities trading terminal, and smart house. The system optionally includes an actuator for effecting the environment of operation, allowing closed-loop feedback operation and automated learning.

Claims

1. A method for selecting electronically deliverable media comprising at least one of semantic, audio and video content, comprising:

receiving a user identification;

identifying, to a computerized interface, a user associated with the user identification;

storing data describing available electronically deliverable media in at least one memory;

persistently storing data representing a plurality of electronically deliverable media which were previously selected by the user in the at least one memory;

automatically performing a search of the stored data describing the available electronically deliverable media, to determine a correspondence of the respective available electronically deliverable media to data representing automatically generated content characteristics comprising automatically extracted at least one of semantic, audio and video content of the electronically deliverable media previously selected by the user, with at least one automated processor;

automatically issuing a notification comprising a list, dependent on a degree of correspondence of characteristics of the available electronically deliverable media, to the data representing automatically generated content characteristics comprising automatically extracted at least one of semantic, audio and video content of the electronically deliverable media previously selected by the user, based on at least the automatically performed search, with the at least one automated processor;

accessing, from a storage device, a user profile based on the user identification;

initiating a personalized startup of the computerized interface based on the user profile;

presenting, through the computerized interface, one or more configuration choices to the user based on a user preference matrix associated with the user profile;

determining, using a confirmation screen, whether an acceptance of the one or more configuration choices is received from the user;

in response to determining that the acceptance of the one or more configuration choices is received, verifying the one or more configuration choices; and

in response to determining that the acceptance of the one or more configuration choices is not received, updating the user preference matrix.

2. The method of claim 1, further comprising receiving, by a voice recognition logic section, a voice pattern of the user, wherein identifying includes recognizing, by the voice recognition logic section, the voice pattern of the user.

3. The method of claim 1, wherein the identified user profile includes information regarding past use of the computerized interface by the user, the method further comprising determining, by a past user history determining element, a past user history of the user.

4. The method of claim 3, wherein the past user history of the user includes derived user preferences, and the user preference matrix is based at least in part on the derived user preferences, the method further comprising presenting the one or more configuration choices to the user based on the derived user preferences.

5. The method of claim 1, further comprising:

determining predicted requirements of the user based at least on the identified user profile; and

presenting, via the computerized interface, a series of screens to the user dependent on the predicted requirements.

6. The method of claim 1, further comprising:

detecting a physical act of the user; and

causing a change in a characteristic of the computerized interface that is proportional to the physical act of the user.

7. The method of claim 6, wherein detecting the physical act of the user further comprises detecting, by at least one of a computer mouse, a two dimensional input device, a trackball, or a remote control device, the physical act of the user.

8. The method of claim 6, wherein detecting the physical act of the user further comprises detecting, by at least one of a joystick, a gyroscope, or a sonic echo-location device, the physical act of the user.

9. The method of claim 6, wherein detecting the physical act of the user further comprises detecting, by at least one of a magnetic location detection device, an electrostatic location detection device, an RF phase location detection device, or a Hallpots device, the physical act of the user.

10. The method of claim 1, further comprising:

detecting, by a voice recognition logic section, a voice input of the user; and

causing a change in a characteristic of the computerized interface in response to the voice input of the user.

11. The method of claim 1, further comprising:

in an absence of the user indicating implicitly or explicitly a knowledge about how to use the computerized interface, inferring that the user is a novice, and prompting the user for only essential items of information with fewer advanced features.

12. The method of claim 1, further comprising:

in response to the user indicating implicitly or explicitly a knowledge about how to use the computerized interface, inferring that the user is an advanced user, and prompting the user with advanced choices and features.

13. The method of claim 1, further comprising color coding the one or more configuration choices, thereby helping to prompt the user as to which data to select or enter.

14. The method of claim 13, further comprising:

color coding instructions or errors with a first color;

color coding data to be entered or that has not been changed with a second color; and

color coding newly entered program data or status information with a third color.

15. The method of claim 1, further comprising:

predicting, based on the identified user profile, the one or more configuration choices;

storing the one or more configuration choices as one or more predicted choices; and

providing, via the computerized interface, a menu selection to allow rejection, by the user, of the one or more predicted choices.

16. The method of claim 15, further comprising:

in response to the user rejecting the one or more predicted choices, presenting next one or more predicted choices to the user.

17. The method of claim 15, further comprising:

in response to the user rejecting the one or more predicted choices, presenting all available choices to the user.

18. The method of claim 1, further comprising:

receiving, from the user, a selection from among the one or more configuration choices; and

updating the identified user profile, stored on the storage device, based on the selection.

19. The method of claim 1, further comprising:

in response to determining that the acceptance of the one or more configuration choices is not received;

receiving a manual input of a configuration choice from the user; and

updating the user preference matrix based on the manual input.

20. The method of claim 1, further comprising filtering a plurality of media streams based on the identified user profile.