Motorola Solutions, Inc.

Aral Sarrafi

Xiao Xiao

Aleksey Lipchin

Sergey Veselkov

Dharanish Kedarisetti

Patrick Henson

Brandon Miles

Mitul Saha

Teresa Dankel

Jeffrey Hunter

Cole Bush

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

A method of detecting anomalous poses is provided, including: detecting an object of interest in a field of view of a video camera; generating, by a neural network, a pose vector associated with a pose of the object; comparing the pose vector to one or more clusters of pose vectors in a dataset of pose vectors, each cluster of pose vectors comprising one or more pose vectors generated from poses of objects; determining a value associated with the similarity of the pose vector to at least one of the one or more pose vectors in the cluster; comparing the value to a predetermined value; and based on the comparison of the value, adding the pose vector to the dataset or generating an alert.

Anomalous pose detection method and system

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Lowell, MA, United States of America

Aral Sarrafi