Abstract:
The various embodiments described herein include methods, devices, and systems for categorizing motion events. In one aspect, a method is performed at a camera device. The method includes: (1) capturing a plurality of video frames via the image sensor, the plurality of video frames corresponding to a scene in a field of view of the camera; (2) sending the video frames to the remote server system in real-time; (3) while sending the video frames to the remote server system in real-time: (a) determining that motion has occurred within the scene; (b) in response to determining that motion has occurred within the scene, characterizing the motion as a motion event; and (c) generating motion event metadata for the motion event; and (4) sending the generated motion event metadata to the remote server system concurrently with the video frames.
Abstract:
A computing system device with processor(s) and memory displays a video monitoring user interface on the display. The video monitoring user interface includes a first region for displaying a live video feed and/or a recorded video feed from the video camera and a second region for displaying a single event timeline. A current video feed indicator is movable on the timeline for indicating the temporal position of the video feed displayed in the first region. The temporal position includes a past time and a current time corresponding to the previously recorded video feed and the live video feed, respectively. While the current video feed indicator is moved to indicate the temporal position of the video feed displayed in the first region, video segments corresponding to the one or more events has a higher priority for display in the first region than video segments that do not contain any event.
Abstract:
The various embodiments described herein include methods, devices, and systems for categorizing motion events. In one aspect, a method includes: (1) obtaining a plurality of video frames, the plurality of video frames corresponding to a scene and a motion event candidate; (2) identifying one or more visual characteristics of the scene; (3) obtaining one or more background factors for the scene; (4) utilizing the obtained background factors to identify one or more motion entities; (5) for each identified motion entity: (a) classifying the motion entity by performing object recognition; and (b) obtaining one or more representative motion vectors based on a motion track of the motion entity; and (6) assigning a motion event category to the motion event candidate based on the identified visual characteristics, the obtained background factors, the classified motion entities, and the obtained representative motion vectors.
Abstract:
A computing system obtains a respective motion vector for each of a series of motion event candidates in real-time as said each motion event candidate is detected in a live video stream. In response to receiving the respective motion vector for each of the series of motion event candidates, the computing system determines a spatial relationship between the respective motion vector of said each motion event candidate to one or more existing clusters established based on a plurality of previously processed motion vectors, and in accordance with a determination that the respective motion vector of a first motion event candidate of the series of motion event candidates falls within a respective range of at least a first existing cluster of the one or more existing clusters, assigns the first motion event candidate to at least a first event category associated with the first existing cluster.
Abstract:
A computing system obtains a respective motion vector for each of a series of motion event candidates in real-time as said each motion event candidate is detected in a live video stream. In response to receiving the respective motion vector for each of the series of motion event candidates, the computing system determines a spatial relationship between the respective motion vector of said each motion event candidate to one or more existing clusters established based on a plurality of previously processed motion vectors, and in accordance with a determination that the respective motion vector of a first motion event candidate of the series of motion event candidates falls within a respective range of at least a first existing cluster of the one or more existing clusters, assigns the first motion event candidate to at least a first event category associated with the first existing cluster.
Abstract:
An electronic device with a display, processor(s), and memory displays a video monitoring user interface including a video feed from a camera located remotely from the client device in a first region and an event timeline in a second region, the event timeline including event indicators for motion events previously detected by the camera. The electronic device detects a user input selecting a portion of the event timeline, where the selected portion of the event timeline includes a subset of the event indicators. In response to the user input, the electronic device causes generation of a time-lapse video clip of the selected portion of the event timeline. The electronic device displays the time-lapse video clip, where motion events corresponding to the subset of the event indicators are played at a slower speed than the remainder of the selected portion of the event timeline.
Abstract:
A computer system processes a video stream to detect a start of a first motion event candidate in the video stream, and in response to detecting the start of the first motion event candidate in the video stream, initiates event recognition processing on a first video segment associated with the start of the first motion event candidate. Initiating the event recognition processing further includes: determining a motion track of a first object identified in the first video segment; generating a representative motion vector for the first motion event candidate based on the motion track of the first object; and sending the representative motion vector for the first motion event candidate to an event categorizer, where the event categorizer assigns a respective motion event category to the first motion event candidate based on the representative motion vector of the first motion event candidate.