ADAPTIVE PATTERN RECOGNITION BASED CONTROLLER APPARATUS AND METHOD AND HUMAN-FACTORED INTERFACE THEREFORE
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.
1 - 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.
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.
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.
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.