Object Video Labs, LLC

Alarm.com Incorporated

Jangwon Lee

Allison Beach

Donald Gerard Madden

Gang Qian

Aaron Lee Roberts

Bret Jutras

Methods and systems for image-based abnormal event detection are disclosed. An example method includes obtaining a sequential set of images captured by a camera; generating a set of observed features for each of the images; generating a set of predicted features based on a portion of the sets of observed features that excludes the set of observed features for a last image in the sequential set of images; determining that a difference between the set of predicted features and the set of observed features for the last image in the sequential set of images satisfies abnormal event criteria; and in response to determining that the difference between the set of predicted features and the set of observed features for the last image in the sequential set of images satisfies abnormal event criteria, classifying the set of sequential images as showing an abnormal event.

Image-based abnormal event detection

A method for classifying activity based on multi-sensor input includes receiving, from two or more sensors, sensor data indicating activity within a building, determining, for each of the two or more sensors and based on the received sensor data, (i) an extracted feature vector for activity within the building and (ii) location data, labelling each of the extracted feature vectors with the location data, generating, using the extracted feature vectors, an integrated feature vector, detecting a particular activity based on the integrated feature vector, and in response to detecting the particular activity, performing a monitoring action.

Activity classification based on multi-sensor input

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for finding lost objects. In some implementations, a request for a location of an item is obtained. Current video data from one or more cameras is obtained. It is determined that the item is not shown in the current video data. Sensor data corresponding to historical video data is obtained. Events that likely occurred with the item and corresponding likelihoods for each of the events are determined. A likely location for the item is determined based on the likelihoods determined for the events. An indication of the likely location of the item is provided.

Investigation system for finding lost objects

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for multi-query object matching based on inverse model frequency. The methods, systems, and apparatus include actions of obtaining images of a sample object, obtaining models of known objects, determining an image score for each pair of the images and the models, determining an inverse model frequency for each image based on the image scores, determining a model score for each model based on the inverse model frequencies and the image scores, and selecting a particular known object of the known objects as the sample object based on the model scores.

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Tysons, VA, United States of America

Jangwon Lee