Google Inc.

Vidiator Enterprises Inc.

Nevengineering, Inc.

Ethernom, Inc.

Ulrich Franz Buddemeier

Hartmut Neven

Hartwig Adam

Fernando A Brucher

Alessandro Bissacco

David Petrou

Charles Joseph Rosenberg

Gabriel Taubman

Karin M Derlich

John Patrick Flynn

Henrik C Stewenius

Lyn Phuong Nguyen

Orang Dialameh

Alexandre Charapov

Hock Thye Law

Tim Dorcey

Imraan Ahmed

Lun Feng Tan

John J Flynn

Luciano Pasquale Agostino Nocera

Randall Ho

David Westwood

James Stewartson

Gregory Patrick Lane Lutter

Frank Paetzold

Yevgeniy V Dzhurinskiy

Systems, devices, and methods for secure data management and transfer for secure data transactions are provided. For example, disclosed herein are secure & tamper resistant smart cards configured to immutably store data and securely exchange at least a portion of the data via, for example, wireless networks and/or peer-to-peer networks. The smart cards comprise a plurality of dedicated hardware circuit blocks electrically coupled via a bus interconnection, the plurality of dedicated hardware circuit blocks configured to authenticate users, verify trust amongst the smart card and external devices, and encrypt sensitive data for secure transmission.

Secure tamper resistant smart card

In one embodiment the present invention is a method for populating and updating a database of images of landmarks including geo-clustering geo-tagged images according to geographic proximity to generate one or more geo-clusters, and visual-clustering the one or more geo-clusters according to image similarity to generate one or more visual clusters. In another embodiment, the present invention is a system for identifying landmarks from digital images, including the following components: a database of geo-tagged images; a landmark database; a geo-clustering module; and a visual clustering module. In other embodiments the present invention may be a method of enhancing user queries to retrieve images of landmarks, or a method of automatically tagging a new digital image with text labels.

Automatic discovery of popular landmarks

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing queries made up of images. In one aspect, a method includes indexing images by image descriptors. The method further includes associating descriptive n-grams with the images. In another aspect, a method includes receiving a query, identifying text describing the query, and performing a search according to the text identified for the query.

Query by image

According to an embodiment, a method for filtering descriptors for visual object recognition is provided. The method includes identifying false positive descriptors having a local match confidence that exceeds a predetermined threshold and a global image match confidence that is less than a second threshold. The method also includes training at least one classifier to discriminate between the false positive descriptors and other descriptors. The method further includes filtering feature point matches using the at least one classifier. According to another embodiment, the filtering step may further include removing one or more feature point matches from a result set. According to a further embodiment, a system for filtering feature point matches for visual object recognition is provided. The system includes a hard false positive identifier, a classifier trainer and a hard false positive filter.

Classifying false positive descriptors

Systems and methods for selecting interest point descriptors for object recognition. In an embodiment, the present invention estimates performance of local descriptors by (1) receiving a local descriptor relating to an object in a first image; (2) identifying one or more nearest neighbor descriptors relating to one or more images different from the first image, the nearest neighbor descriptors comprising nearest neighbors of the local descriptor; (3) calculating a quality score for the local descriptor based on the number of nearest neighbor descriptors that relate to images showing the object; and (4) determining, on the basis of the quality score, if the local descriptor is effective in identifying the object.

Systems and methods for selecting interest point descriptors for object recognition

Aspects of the invention pertain to matching a selected image/photograph against a database of reference images having location information. The image of interest may include some location information itself, such as latitude/longitude coordinates and orientation. However, the location information provided by a user's device may be inaccurate or incomplete. The image of interest is provided to a front end server, which selects one or more cells to match the image against. Each cell may have multiple images and an index. One or more cell match servers compare the image against specific cells based on information provided by the front end server. An index storage server maintains index data for the cells and provides them to the cell match servers. If a match is found, the front end server identifies the correct location and orientation of the received image, and may correct errors in an estimated location of the user device.

Matching an approximately located query image against a reference image set

According to an embodiment, a method for filtering feature point matches for visual object recognition is provided. The method includes identifying local descriptors in an image and determining a self-similarity score for each local descriptor based upon matching each local descriptor to its nearest neighbor descriptors from a descriptor dataset. The method also includes filtering feature point matches having a number of local descriptors with self-similarity scores that exceed a threshold. According to another embodiment, the filtering step may further include removing feature point matches. According to a further embodiment, a system for filtering feature point matches for visual object recognition is provided. The system includes a descriptor identifier, a self-similar descriptor analyzer and a self-similar descriptor filter.

Self-similar descriptor filtering

Methods for grouping images from image corpora using graph clustering are presented. In one embodiment, a method is presented where grouping of images from a collection of digital images is done by: representing regions of images as vertices in a graph; connecting each pair of matching-vertices with a matching-edge; connecting each pair of overlap-vertices with an overlap-edge; assigning weights to each said matching-edge and to each said overlap-edge; clustering the graph, wherein clustering generates one or more vertex-clusters; and grouping the digital images into visual-clusters based on the vertex-clusters. Corresponding systems and computer program products are also presented.

Clustering images using an image region graph

Growing community of inventors

Venice, CA, United States of America

Ulrich Franz Buddemeier