Future Wei Technologies, Inc.

Huawei Technologies Co., Limited

Xin Xin

Aggelos K Katsaggelos

Zhu Li

Object recognition can be improved by verifying a geometric consistency between matching interesting points pairs of two images, as objects with the images are more likely to match when the matching interesting points pairs are geometrically consistent. The geometric consistency between matching interesting points pairs can be verified in accordance with a topology code distance vector (D). The topology code distance vector (D) may be evaluated in accordance with a decision tree classifier, which may be trained in accordance with previous or historic topology code distance vectors. The topology code distance vector (D) may be computed from a subset of matching interesting points pairs having the shortest matching distance.

System and method for randomized point set geometry verification for image identification

A system and a method for progressive queries, which are a sequence of queries for visual search of an image, sent from a sender to a receiver of a communication network, are disclosed. Queries based on a set of feature points and their associated locations of an image may be selected in sequence. A sender sends a first query to a receiver, wherein the first query comprises a number of feature points which is a subset of the set of feature points of the image invariant to rotation and scaling in creating the image. The sender receives a feedback from the receiver, wherein the feedback is generated by the receiver based on searching an image repository using information from the first query. The sender then decides whether there is a match of the image in the image repository based on the received feedback.

Scalable query for visual search

A method and an apparatus for processing an image generates, using a linear embedding operator, a second set of feature points from a first set of feature points of the image, so that a pair-wise nearest neighbor (NN) topological relationship among the first set of feature points is preserved in the second set of feature points. The linear embedding operator is determined by an affinity model comprising a first affinity parameter, a second affinity parameter, and an affinity matrix, wherein a sparsity of the affinity matrix is controlled by the first affinity parameter and the second affinity parameter.

System and method for compact descriptor for visual search

A method and an apparatus for processing an image generate a first vector of a first number dimension for the image from a first number of points of the image based on topological information of the first number of points, and the first vector for the image is invariant to rotation and scaling in creating the image. The first number of points may be locations of a set of rotation and scaling invariant feature points for the image, and the generated first vector may be a graph spectrum of a pair-wise distance matrix generated from the first number of points of the image.

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Chicago, IL, United States of America

Xin Xin