Abstract: 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.

Abstract: 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.

Abstract: 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.