System, method and application for the recognition, verification and similarity ranking of facial or other object patterns
First Claim
1. A system for determining the likelihood that two object patterns arise from the dame object source, said system comprising:
- a. means for receiving first and second object patterns each including a plurality of feature components having a plurality of values;
b. Means for assigning a predetermined weight to each said feature component in each of said object patterns, wherein the assigned weights are one of a plurality of weights in corresponding first and second weight sets in a neural network, wherein each weight set includes a plurality of weight subsets, each weight subset corresponding to the location of one of said feature components, wherein particular weights in each subset are assigned according to the value of the component; and
c. means for determining an output of said neural network by calculating a comparison function of the assigned weights in the two respective weight sets, wherein the values of the weights are predetermined such that the output is a measure of the likelihood that two object patterns arise from the same object source, wherein the value of said predetermined weights are derived from a training procedure and are independent of the value of the feature component.
2 Assignments
0 Petitions
Accused Products
Abstract
A system and method is disclosed for determining the likelihood that two object patterns arise from the same object source. It is able to do this without having previously been exposed to either of the object patterns. This system utilizes an adaptive processor trained to make this determination using a large number of example patterns in different views and orientations. It accommodates large verifications of how an object source is presented in an image. The system also does not require the storage of any information about any particular pattern, which greatly minimizes the storage requirements and improves the throughput of the system. Further, there is no need for accessing a database of previously stored features from a given pattern source. The system is particularly useful for object patterns which consist of facial images. The system employs a new technique for locating an object of interest within a pattern using an adaptive processor to determine a region of interest. The technique is resistant to irrelevant overlapping patterns. The system and method of the present invention employ a technique for performing authentication of the validity of a card or a user'"'"'s image on a computer network system which has a user'"'"'s face image stored within. Finally, this invention provides a new technique for naturally aligning the face. This technique, which is convenient to use and yields candid shots, is useful in facial verification.
236 Citations
12 Claims
-
1. A system for determining the likelihood that two object patterns arise from the dame object source, said system comprising:
-
a. means for receiving first and second object patterns each including a plurality of feature components having a plurality of values; b. Means for assigning a predetermined weight to each said feature component in each of said object patterns, wherein the assigned weights are one of a plurality of weights in corresponding first and second weight sets in a neural network, wherein each weight set includes a plurality of weight subsets, each weight subset corresponding to the location of one of said feature components, wherein particular weights in each subset are assigned according to the value of the component; and c. means for determining an output of said neural network by calculating a comparison function of the assigned weights in the two respective weight sets, wherein the values of the weights are predetermined such that the output is a measure of the likelihood that two object patterns arise from the same object source, wherein the value of said predetermined weights are derived from a training procedure and are independent of the value of the feature component. - View Dependent Claims (2, 3, 4, 5, 6)
-
-
7. A method for determining the likelihood that two object patterns arise from the same object source, said method comprising:
-
a. receiving first and second object patterns each including a plurality of feature components having different values; c. assigning a predetermined weight to each said feature component in each of said object patterns, wherein the assigned weights are one of a plurality of weights in corresponding first or second weight sets in a neural network, wherein each weight set includes a plurality of weight subsets, each weight subset corresponding to the location of one of said feature components, wherein particular weights in each subset are assigned according to the value of the component; and d. determining an output of said neural network by calculating a comparison function of the assigned weights in the two respective weight sets, wherein the values of the weights are predetermined such that the output is a measure of the likelihood that two object patterns arise from the same object source, and wherein the value of said predetermined weights are derived from a training procedure and are independent of the value of the feature component. - View Dependent Claims (8, 9, 10, 11, 12)
-
Specification