ADAPTIVE PATTERN RECOGNITION BASED CONTROLLER APPARATUS AND METHOD AND HUMAN-FACTORED INTERFACE THEREFORE

• US 20110029922A1
• Filed: 07/09/2007
• Published: 02/03/2011
• Est. Priority Date: 12/23/1991
• Status: Abandoned Application

• Current Assignee: Hoffberg Family Trust 2, Blanding Hovenweep LLC (Intellectual Ventures LLC), STEVEN M. HOFFBERG 2004-1 GRAT
• Original Assignee: Hoffberg Family Trust 2
• Inventors: Hoffberg, Linda Irene, Hoffberg, Steven M.
• Application Number:
  US11/775,222
• Publication Number:
  US 20110029922A1
• Time in Patent Office: Days
• US Class Current: 715/811
• CPC Class Codes: G05B 19/0426 Programming the control sequence
• CPC Class Codes: G05B 2219/23026 Recognise user input pattern and present possible intended program
• CPC Class Codes: G05B 2219/24162 Biometric sensor, fingerprint as user access password
• CPC Class Codes: G05B 2219/2613 Household appliance in general
• CPC Class Codes: G05B 2219/2615 Audio, video, tv, consumer electronics device
• CPC Class Codes: G06F 3/048 Interaction techniques based on graphical user interfaces [GUI]
• CPC Class Codes: G06V 40/103 Static body considered as a whole, e.g. static pedestrian or occupant recognition
• CPC Class Codes: H04N 21/4131 home appliance, e.g. lighting, air conditioning system, metering devices home automation data switching networks exchanging configuration information on appliance services H04L12/2807
• CPC Class Codes: H04N 21/42203 sound input device, e.g. microphone
• CPC Class Codes: H04N 21/42204 User interfaces specially adapted for controlling a client device through a remote control device; Remote control devices therefor constructive details of casings for the remote control device H01H9/0235; user interfaces for controlling a tuning device of a television receiver through a remote control H03J9/00; remote control of peripheral devices connected to a television receiver through the remote control device of the television receiver H04B1/205
• CPC Class Codes: H04N 21/42221 Transmission circuitry, e.g. infrared [IR] or radio frequency [RF]
• CPC Class Codes: H04N 21/4223 Cameras H04N23/00 takes precedence
• CPC Class Codes: H04N 21/4263 involving specific tuning arrangements, e.g. two tuners
• CPC Class Codes: H04N 21/4332 by placing content in organized collections, e.g. local EPG data repository interfaces, Database management systems or updating for information retrieval G06F16/23; details of retrieval of video data and associated meta data in video database G06F16/739
• 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 21/43637 involving a wireless protocol, e.g. Bluetooth, RF or wireless LAN [IEEE 802.11] arrangements for wireless networking or broadcasting of information in indoor or near-field type systems H04B10/114
• CPC Class Codes: H04N 21/4394 involving operations for analysing the audio stream, e.g. detecting features or characteristics in audio streams arrangements characterised by components specially adapted for monitoring, identification or recognition of audio in broadcast systems H04H60/58
• 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 21/44016 involving splicing one content stream with another content stream, e.g. for substituting a video clip
• CPC Class Codes: H04N 21/4415 using biometric characteristics of the user, e.g. by voice recognition or fingerprint scanning cryptography using biological data H04L9/3231; authentication in networks using biometric H04L63/0861
• CPC Class Codes: H04N 21/44218 : Detecting physical presence or behaviour of the user, e.g. using sensors to detect if the user is leaving the room or changes his face expression during a TV program methods or arrangements for recognising human body or animal bodies or body parts G06V40/10; methods or arrangements for acquiring or recognising human faces, facial parts, facial sketches, facial expressions G06V40/16; methods or arrangements for recognising movements or behaviour G06V40/20; arrangements for identifying users in broadcast systems H04H60/45
• 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 21/4622 : Retrieving content or additional data from different sources, e.g. from a broadcast channel and the Internet web site content organization and management for information retrieval from the Internet G06F16/958; transmission by internet of broadcast information H04H60/82; stock exchange data over packet-switching network H04L12/1804; push services including data channel over packet-switching network H04L12/1859
• 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 21/4667 : 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 21/47 : End-user applications
• CPC Class Codes: H04N 21/4753 : for user identification, e.g. by entering a PIN or password cryptographic authentication protocols H04L9/32; networks authentication protocols H04L63/08
• CPC Class Codes: H04N 21/4788 : communicating with other users, e.g. chatting arrangements for providing for computer conferences, e.g. chat rooms, to substation in data switching networks H04L12/1813; distributed application using peer-to-peer [P2P] networks H04L67/104
• CPC Class Codes: H04N 21/4826 : using recommendation lists, e.g. of programs or channels sorted out according to their score
• CPC Class Codes: H04N 21/812 : involving advertisement data advertising per se G06Q30/02
• CPC Class Codes: H04N 5/765 : Interface circuits between an apparatus for recording and another apparatus
• CPC Class Codes: H04N 5/782 : on tape
• CPC Class Codes: H04N 5/84 : using optical recording H04N5/80, H04N5/89, H04N5/91 take precedence
• CPC Class Codes: H04N 9/8042 : involving data reduction

Abstract

The need for a more readily usable interface for programmable devices is widely recognized. The present invention relates to programmable sequencing devices, or, more particularly, the remote controls for consumer electronic devices. The present invention provides an enhanced interface for facilitating human input of a desired control sequence in a programmable device by employing specialized visual feedback. The present invention also relates to a new interface and method of interfacing with a programmable device, which is usable as an interface for a programmable video cassette recorder.

Claims

1-107. -107. (canceled)

108. A method of classifying a pattern, said method comprising the steps of:

acquiring a signal, said signal including an input pattern to be classified;

performing at least one wavelet-based transform on at least a portion of said input pattern, to produce a wavelet transformed pattern;

defining a compressed data encoded representation based on the wavelet transformed pattern; and

classifying the pattern on the basis of said compressed data encoded representation.

109. The method as claimed in claim 108, wherein said step of classifying said input pattern on the basis of said compressed data encoded representation comprises the step of classifying an object represented in an image on the basis of said compressed data encoded representation.

110. An apparatus for classifying a patter, comprising;

a memory for storing a signal;

a processor adapted to perform a wavelet transform on at least a portion of said stored signal, to produce a wavelet transformed pattern;

said processor being further adapted to define a compressed data encoded representation of the signal based on the wavelet transformed pattern; and

said processor being further adapted to classify the pattern on the basis of said compressed data encoded representation.

111. An apparatus as claimed in claim 110, wherein said signal comprises a video representation of at least one physical object.

112. An apparatus as claimed in claim 110, wherein said processor classifies said compressed data encoded representation based on a plurality of templates.

113. A system for presenting a program to a viewer, comprising:

a source of program material;

a memory for storing received program material; and

a processor for selectively processing the program material based on a correlation between a viewer preference and a characterization of the content of the program material.

114. The system according to claim 113, wherein said selectively processing is selected from one or more of the group consisting of persistently storing the program material, outputting the program material separately from unselected program material, updating a user preference profile, and deleting the program material from temporary storage.

116. The method according to claim 113, wherein said selectively processing is selected from one or more of the group consisting of persistently storing the program material, outputting the program material separately from unselected program material, updating a user preference profile, and deleting the program material from temporary storage.

115. A method for presenting a program to a viewer, comprising:

receiving a source of program material;

storing received program material in a memory; and

selectively processing the program material based on a computed correlation between a stored viewer preference expressed as a preference profile data construct and a stored digital data characterization of the content of the program material.

117. A method of classifying a signal, comprising the steps of:

receiving a signal comprising a representation of an object to be classified;

performing at least one of a wavelet transform and a fractal transform on a representation of the signal, to produce a transformed representation;

normalizing at least one of the signal and the transformed representation of the signal to produce a normalized transformed representation;

determining a relation between the normalized transformed representation and a plurality of templates stored in a database; and

classifying the object based on said determining step.

118. The method according to claim 117, wherein said normalizing comprises performing at least one Affine transform.

119. The method according to claim 117, wherein said signal comprises a representation of at least one of an object in an image.

120. The method according to claim 117, wherein said signal comprises a representation of at least one of an object in a video sequence.

121. The method according to claim 117, wherein the object comprises a source of sound, and wherein said signal comprises a representation of at least one sound.

122. The method according to claim 117, wherein the signal is segmented into a plurality of regions, and wherein said determining is performed for each of said plurality of regions.

123. The method according to claim 117, wherein said determining comprises determining a distance between a classification template and a portion of the normalized transformed representation of the signal.

124. The method according to claim 117, wherein the signal comprises a plurality of object representations, and wherein said determining is performed for each of said plurality of object representations, further comprising the step of producing a composite classification of the signal.

125. The method according to claim 117, wherein the signal comprises a texture, further comprising the step of classifying the texture.

126. The method according to claim 117, further comprising the step of identifying the object.

127. The method according to claim 117, wherein at least one of the transformed representation and the normalized transformed representation is stored as a compressed digital representation of the signal, and said determining is performed on the compressed digital representation.