Avigilon Corporation

Motorola Solutions, Inc.

Nicholas John Alcock

Brenna Randlett

Aleksey Lipchin

Roger David Donaldson

Tulio De Souza Alcantara

Xiao Xiao

Seyedmostafa Azizabadifarahani

Peter L Venetianer

Mahesh Saptharishi

Jehan Wickramasuriya

Shaun P Marlatt

Yanyan Hu

Kevin Piette

Moussa Doumbouya

Alexander Chau

Lu He

Dharanish Kedarisetti

Ken Jessen

Quan Pan

Kurt Russell Grossnickle

Hao Zhang

Liam Alexander Scholte

Zachary Aaron Weingarten

Liia Fadeeva

Eric Peterson

Hugo Fitzpatrick

Justin Alexander Byfield

Obtaining potential match results for a reference image across a plurality of system sites is disclosed. A computing device of one of the system sites includes a signature generator identifiable as a first version amongst a plurality of versions of a respective plurality of possible signature generators. The computing device is configured to generate, within the first signature generator, a first signature corresponding to a cropped object portion of a larger image. The first signature is distinctive to the first version. The computing device is further configured to determine that the cropped object portion being processed within the computing device is a match result for a similar images search. A server is configured to receive the cropped object portion and the first signature from the computing device.

Obtaining potential match results for a reference image across a plurality of system sites

A method of detecting unusual motion is provided, including: determining features occurring during a fixed time period; grouping the features into first and second subsets of the fixed time period; grouping the features in each of the first and second subsets into at least one pattern interval; and determining when an unusual event has occurred using at least one of the pattern intervals.

Unusual motion detection method and system

A method and system for processing images for a search is provided, including: receiving a plurality of images selected from search results; for each image in the plurality of images, retrieving a feature vector associated with the image; selecting a subset of the feature vectors based on similarity of feature vectors associated with the images in the plurality of images; and performing a search for feature vectors in a database similar to the feature vectors in the subset of feature vectors.

System and method for improving speed of similarity based searches

Techniques for notification are presented. The techniques may include detecting a natural language phrase concerning an event at a geographic location in speech broadcast by a radio system, determining at least one search criteria from the natural language phrase, searching video surveillance data based on the at least one search criteria, such that search results are obtained, forming computer generated speech corresponding to the search results, and delivering the computer generated speech audibly.

Speech-based two-way radio assistant

There are described methods and systems for facilitating identification of an object-of-interest. A face similarity score and a body similarity score of a query image relative to a gallery image are determined. A fused similarity score of the query image relative to the gallery image is determined by applying a relationship between the face similarity score, the body similarity score, and the fused similarity score. The fused similarity score is indicative of whether or not the object-of-interest and the potential object-of-interest are the same object-of-interest. For example, a machine learning process is used to fuse the face similarity score and the body similarity into the fused similarity score. The process is repeated for multiple gallery images. The gallery images may then be ranked according to their respective fused similarity scores.

Method and system for facilitating identification of an object-of-interest

Methods, systems, and techniques for performing a hash-based appearance search. A processor is used to obtain a hash vector that represents a search subject that is depicted in an image. The hash vector includes one or more hashes as a respective one or more components of the hash vector. The processor determines which one or more of the hashes satisfy a threshold criterion and which one or more of the components of the hash vector qualify as a scoring component. The one or more components that qualify correspond to a respective one or more hashes that satisfy the threshold criterion and that are represented in a scoring database that is generated based on different examples of a search target. The processor determines a score representing a similarity of the search subject to the different examples of the search target.

Hash-based appearance search

Growing community of inventors

Vancouver, Canada

Nicholas John Alcock