초록 ▼

A system for automatically detecting and recognizing the identity of a deformable object such as a human face, within an arbitrary image scene. The system comprises an object detector implemented as a probabilistic DBNN, for determining whether the object is within the arbitrary image scene and a fe

A system for automatically detecting and recognizing the identity of a deformable object such as a human face, within an arbitrary image scene. The system comprises an object detector implemented as a probabilistic DBNN, for determining whether the object is within the arbitrary image scene and a feature localizer also implemented as a probabilistic DBNN, for determining the position of an identifying feature on the object such as the eyes. A feature extractor is coupled to the feature localizer and receives coordinates sent from the feature localizer which are indicative of the position of the identifying feature and also extracts from the coordinates information relating to other features of the object such as the eyebrows and nose, which are used to create a low resolution image of the object. A probabilistic DBNN based object recognizer for determining the identity of the object receives the low resolution image of the object inputted from the feature extractor to identify the object.

대표청구항 ▼

[ We claim:] [1.] A system for automatically detecting and recognizing the identity of a deformable object within an arbitrary image scene, said system comprising:object detector means for determining whether said object is within said arbitrary image scene;feature localizer means for determining th

[ We claim:] [1.] A system for automatically detecting and recognizing the identity of a deformable object within an arbitrary image scene, said system comprising:object detector means for determining whether said object is within said arbitrary image scene;feature localizer means for determining the position of an identifying feature on said object, said feature locator means being coupled to said object detector means;feature extractor means coupled to said feature localizer, for receiving coordinates sent from said feature localizer which are indicative of the position of said identifying feature and for extracting from said coordinates information relating to other features of said object which is used to create a low resolution image of said object; andobject recognizer means for determining the identity of said object, said object recognizer means being coupled to said feature extractor means and being operative to receive said low resolution image of said object inputted from said feature extractor means to identify said object;wherein said object detector means, said feature localizer means, and said object recognizer means are each implemented in a decision-based neural network;wherein said decision-based neural network comprises a one-class-in-one network structure having a plurality of subnets and a plurality of classes, wherein each one of said subnets is designated to one of said classes in order to distinguish it from said other classes; andwherein said decision-based neural network includes a training scheme having a first phase and a second phase, wherein said first phase includes individually training each of said subnets without mutually exchanging information between said classes and said second phase includes reinforcing learning and anti-reinforcing learning obtained during said first phase.