Abstract: The various implementations described herein include systems and methods for recognizing persons in video streams. In one aspect, a method includes: (1) obtaining images collected by video cameras in a smart home environment, each image including a detected person; (2) for each image, obtaining personally identifiable information of the detected person, the personally identifiable information generated from analysis of the image; (3) grouping the images into a first group of a plurality of groups based on the personally identifiable information, each group of the plurality of groups representing a unique person; (4) receiving from a user a request to remove a first image from the first group; and (5) in response to the request: (a) removing the first image from the first group; and (b) disassociating the corresponding personally identifiable information from the first group.

Abstract: The various implementations described herein include systems and methods for recognizing persons in video streams. In one aspect, a method includes: (1) obtaining a live video stream; (2) detecting person(s) in the stream; and (3) determining, from analysis of the live video stream, personally identifiable information of the detected person(s); (4) determining, based on the personally identifiable information, that the first person is not known to the computing system; (5) in accordance with the determination that the first person is not known: (a) storing the personally identifiable information; and (b) requesting a user to classify the first person; and (6) in accordance with (i) a determination that a predetermined amount of time has elapsed since the request was transmitted and a response was not received, or (ii) a determination that a response was received classifying the first person as a stranger, deleting the stored personally identifiable information.

Abstract: The various embodiments described herein include methods, devices, and systems for providing event alerts. In one aspect, a method includes: (1) obtaining a video feed, the video feed comprising a plurality of images; and, (2) for each image, analyzing the image to determine whether the image includes a person, the analyzing including: (a) determining that the image includes a potential instance of a person by analyzing the image at a first resolution; (b) in accordance with the determination that the image includes the potential instance, denoting a region around the potential instance; (c) determining whether the region includes an instance of the person by analyzing the region at a second resolution, greater than the first resolution; and (d) in accordance with a determination that the region includes the instance of the person, determining that the image includes the person.

Abstract: The various embodiments described herein include methods, devices, and systems for categorizing motion event candidates. In one aspect, a method includes receiving and processing video frames that include a motion event candidate. The processing includes: (a) obtaining background factors corresponding to a background in at least a subset of the video frames; (b) utilizing the background factors to identify one or more motion entities; (c) for each motion entity, obtaining one or more representative motion vectors based on a motion track of the respective motion entity; (d) identifying one or more features in at least a subset of the video frames; and (e) aggregating the background factors, the representative motion vectors, and the features to generate motion features. The method further includes sending the motion features to an event categorizer, where the event categorizer assigns a motion event category to the motion event candidate based on the received motion features.