Motorola Solutions, Inc.

Avigilon Corporation

Xiao Xiao

Aleksey Lipchin

Nicholas John Alcock

Tulio De Souza Alcantara

Brenna Randlett

Aral Sarrafi

Peter L Venetianer

Sergey Veselkov

Burak Kakillioglu

Cole Bush

Brandon Miles

Mitul Saha

Jeffrey Hunter

A device, method and system for identifying objects in warped images from a fisheye camera is provided. A device converts warped images from a fisheye camera into dewarped images. The device determines that a first object identified in the dewarped images is: entering a blind-spot region of the dewarped images; or located at a first edge region of the dewarped images. The device determines that a second object is: exiting the blind-spot region of the dewarped images, or located at a second edge region of the dewarped images, the second edge region opposite the first edge region. The device, in response to the second object meeting one or more reidentification conditions associated with the first object, reidentifies the second object as the first object at the dewarped images.

Device, method and system for identifying objects in warped images from a fisheye camera

A method, system and computer program product for divided processing in providing object detection focus is disclosed. The system includes a first video analytics determinator configured to provide, by infrequent employment thereof within the system, a partial object detection focus in first information that informs as to where moving objects are likely and unlikely to appear within video frames in respect of video. The system also includes a second video analytics determinator configured to: informatively employ the first information to determine a refined object detection focus; and provide the refined tracking and/or object detection focus in second information.

Method, system and computer program product for divided processing in providing object detection focus

One aspect provides a method for object detection including detecting, using an electronic processor, a plurality of candidate objects in a video using a convolutional neural network detection process and a background subtraction detection process and identifying, using the electronic processor, a candidate object from the plurality of candidate objects. The candidate object detected by the background subtraction detection process in a location of the video with no candidate objects detected by the convolutional neural network detection process. The method also includes determining, using the electronic processor, a background subtraction confidence level of the candidate object and categorizing, using the electronic processor, the candidate object as a detected object in the video in response to the background subtraction confidence level satisfying a background subtraction confidence threshold.

Hybrid video analytics for small and specialized object detection

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

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Reading, MA, United States of America

Xiao Xiao