The various implementations described herein include methods, devices, and systems for detecting motion and persons. In one aspect, a method is performed at a smart home system that includes a video camera, a server system, and a client device. The video camera captures video and audio, and wirelessly communicates, via the server system, the captured data to the client device. The server system: (1) receives and stores the captured data from the video camera; (2) determines whether an event has occurred, including detected motion; (3) in accordance with a determination that the event has occurred, identifies video and audio corresponding to the event; and (4) classifies the event. The client device receives information indicative of the identified events, displays a user interface for reviewing the video and audio stored by the remote server system, and displays the at least one classification for the event.

A method and a system for distributing load in a network including a requesting node and a set of external processing nodes are disclosed. The method comprises sending an Internet Control Message Protocol (ICMP) message to each external processing node of the set of external processing nodes. The method further comprises identifying one or more external processing nodes from the set of external processing nodes as responding nodes based on a receipt of response to a corresponding ICMP message thereto. The method further comprises selecting an external processing node from the identified responding nodes as a most suitable external processing node having capability to fulfill a video processing request submitted by the requesting node. The method further comprises sending a transmission package from the requesting node to the selected external processing node for processing thereof. The method further comprises receiving a binary response from the selected external processing node.

This disclosure describes, in part, an audio/video (A/V) device that includes a first camera for generating first image data and one or more second cameras for both motion detection and generating second image data. For instance, the A/V device may generate and then store the second image data in one or more buffers. The A/V device may then detect an event, such as possible motion of an object. Based on detecting the event, A/V device may cause the one or more second cameras to cease generating the second image data and cause the first camera to begin generating the first image data. The A/V device may then process the second image data and send the processed second image data to a computing system. Next, the A/V device may process the first image data and send the processed first image data to the computing system.

An image processing apparatus includes, an input unit configured to input images, a first detection unit configured to detect a first area based on features in the images input by the input unit, a second detection unit configured to detect a second area based on variations between the images input by the input unit, a generation unit configured to generate a background image by using a result of the first area detection by the first detection unit and a result of the second area detection by the second detection unit, and a processing unit configured to perform image processing for reducing a visibility of a specific region identified through a comparison between a processing target image acquired after a generation of the background image by the generation unit and the background image.

The present application describes a system and method for extending a range of an image detection and classification system that is associated with various image capture devices. The range of the image detection and classification system is extended using one or more of an optical zoom on an area of interest, a digital zoom on the area of interest and a crop operation on the area of interest.

A system, method and apparatus for configuring a person detection sensor. The person detection sensor may limit its transmissions in accordance with a pre-configured dwell time. The person detection sensor may receive a new dwell time from a personal communication device. When the new dwell time is received, it is stored in memory and is then used to regulate the number of transmissions of the person detection sensor in accordance with the new dwell time.

The present disclosure relates to a method performed by a background blurring system (1) for provision of a video compression stream from a video camera (2) adapted for capturing a scene. The background blurring system identifies (1001) in a first image of the scene, at a first point in time, at least a first pixel comprised in a background of the first image. The background blurring system further determines (1002) a blurred pixel value for the at least first pixel. Moreover, the background blurring system provides (1003), subsequent the first point in time, the blurred pixel value in the video compression stream. The background blurring system furthermore identifies (1004) in a second image of the scene, at a subsequent second point in time, that the at least first pixel has altered to be comprised in a foreground of the second image. Moreover, the background blurring system provides (1005) in the video compression stream, subsequent the second point in time—continuously and/or intermittently—identified non-blurred pixel values for the at least first pixel. The background blurring system further identifies (1006) in a third image of the scene, at a subsequent third point in time, that the at least first pixel has altered to be comprised in a background of the third image, wherein a value of the at least first pixel has remained unchanged from an intermediate point in time up to the third point in time. Furthermore, when the third point in time is within a predeterminable background merge time period from the intermediate point in time, the background blurring system provides (1007), subsequent the third point in time, the blurred pixel value in the video compression stream. The disclosure also relates to a background blurring system in accordance with the foregoing, a video camera comprising such a background blurring system, and a respective corresponding computer program product and non-volatile computer readable storage medium.

Various embodiments concern video patient monitoring with detection zones. Various embodiments can comprise a camera, a user interface, and a computing system. The computing system can be configured to perform various steps based on reception of a frame from the camera, including: calculate a background luminance of the frame; monitor for a luminance change of a zone as compared to one or more previous frames, the luminance change indicative of patient motion in the zone; and compare the background luminance to an aggregate background luminance, the aggregate background luminance based on the plurality of frames. If the background luminance changed by more than a predetermined amount, then the aggregate background luminance can be set to the background luminance, luminance information of the previous frames can be disregarded, and motion detection can be disregarded.

A system, method and apparatus for configuring a person detection sensor. The person detection sensor may limit its transmissions in accordance with a pre-configured dwell time. The person detection sensor may receive a new dwell time from a personal communication device. When the new dwell time is received, it is stored in memory and is then used to regulate the number of transmissions of the person detection sensor in accordance with the new dwell time.

A building system can operate to receive a request to generate a video tracking movement of an entity throughout the building. The building system can operate to search, based on a building graph, a database for a set of images or videos of cameras of the building that track the entity throughout the building. The building graph can include nodes indicating spaces of the building and the cameras of the building. The building graph can include building graph including edges between the nodes representing relationships between the spaces and the cameras. The building system can operate to join the set of images or videos together to create the video.