An indoor camera includes: an image capturing unit; a storage unit configured to store at least one detection area in association with stagnation times, the detection area that is a target area for detecting stagnation of a pet, and the stagnation times indicating the number of times when the pet enters the detection area and stagnates in the detection area; and a processor configured to detect a position of the pet and count the stagnation times of the pet in the detection area based on captured images. If determining, based on the captured images, that the pet stagnates in the detection area for a predetermined time period or longer, the processor increments and counts the stagnation times of the pet in the detection area and generates an action log including identification information of the detection area and information on the stagnation times.

Various implementations disclosed herein include devices, systems, and methods that enable improved display of virtual content in computer generated reality (CGR) environments. In some implementations, the virtual content includes a reminder associated with a user and the user's physical environment.

A system for identifying a location of one or more assets in a predefined two-dimensional area comprises at least three tracking stations and one or more tracking tags. Each tracking station selectively emits a vertical laser line upon which is embedded a unique identifier, selectively sweeps its laser line about its central axis such that each tracking station's laser line sweeps across at least a portion of the predefined 2-D area, and selectively transmits a current angle of its laser line as its laser line sweeps about its central axis. Each tracking tag detects a laser line from at least three tracking stations within its line of sight. Each tracking tag decodes the unique tracking station identifier, receives the current angle from the tracking station corresponding to the detected laser line, and stores the decoded unique tracking station identifier and the received current angle.

A system for identifying a location of one or more assets in a predefined two-dimensional area comprises at least three tracking stations and one or more tracking tags. Each tracking station selectively emits a vertical laser line upon which is embedded a unique identifier, selectively sweeps its laser line about its central axis such that each tracking station's laser line sweeps across at least a portion of the predefined 2-D area, and selectively transmits a current angle of its laser line as its laser line sweeps about its central axis. Each tracking tag detects a laser line from at least three tracking stations within its line of sight. Each tracking tag decodes the unique tracking station identifier, receives the current angle from the tracking station corresponding to the detected laser line, and stores the decoded unique tracking station identifier and the received current angle.

Alignment systems and methods are disclosed. A system includes a first component and a second component. The first component has a first body supporting a first alignment member. The second component has a second body supporting a second alignment member. The first and second alignment members are separated from another and are configured to provide an indication that a fluoroscopic device is properly aligned with an anatomical plane when viewed under fluoroscopy. A method includes placing a first component supporting a first alignment member and a second component supporting a second alignment member relative to a patent, and aligning a fluoroscopic device with an anatomical plane using the first and second alignment members.

A building appraisal system conducted by a remote inspector located away from a building. A remote user connected to a user on site can share images, measurements and other data to conduct an examination of the building such as an appraisal. A processor coupled to an image sensor can be configured to receive a gross floor area of the building. Images of an interior room of the building are stored in memory. The processor determines a planar surface in the images corresponding to a floor surface of the interior room and a plurality of corners in the images forming vertices of a bounded floor area on the floor surface. The processor can compute an adjusted floor area of the building that includes the bounded floor area subtracted from the gross floor area.

In general, platforms, systems, and methods are provided for identifying and privacy protecting authorized persons, vehicles, and objects in motion in the field of view of a video security camera or set of networked security cameras for use in a residential or business community. Various embodiments incorporate a security identification system that includes one or more mobile devices such as a smartphone or smartwatch, one or more cameras situated within a community with processors connected to data centers via the internet, and software running a cloud service infrastructure communicating to both the smartphone or smartwatch. The system can also include the ability to translate locational information from a smartphone or smartwatch into corresponding identification and geolocation information on images from security cameras.

A method and system, the method including transmitting a unique identifier of at least one radio frequency (RF) transmitter to a device in a vicinity of the RF transmitter; acquiring images of objects by a vision system, the vision system comprising at least one image capturing device and an image processing unit to determine objects in the images acquired by the image capturing device; determining, by a controller, a location of the device based on, at least in part, the unique identifier of one of the at least one RF transmitters; and determining, by the controller, a precise location of the device based on a correlation between the location of the device determined based on the unique identifier and the objects captured in the images acquired by the image capturing device.

A method and system, the method including transmitting a unique identifier of at least one radio frequency (RF) transmitter to a device in a vicinity of the RF transmitter; acquiring images of objects by a vision system, the vision system comprising at least one image capturing device and an image processing unit to determine objects in the images acquired by the image capturing device; determining, by a controller, a location of the device based on, at least in part, the unique identifier of one of the at least one RF transmitters; and determining, by the controller, a precise location of the device based on a correlation between the location of the device determined based on the unique identifier and the objects captured in the images acquired by the image capturing device.

A method of obtaining a head-related transfer function for a user is provided. The method comprises generating an audio signal for output by a handheld device and outputting the generated audio signal at a plurality of locations by moving the handheld device to those locations. The audio output by the handheld device is detected at left-ear and right-ear microphones. A pose of the handheld device relative to the user's head is determined for at least some of the locations. One or more personalised HRTF features are then determined based on the detected audio and corresponding determined poses of the handheld device. The one or more personalised HRTF features are then mapped to a higher-quality HRTF for the user, wherein the higher-quality HRTF corresponds to an HRTF measured in an anechoic environment. This mapping may be learned using machine learning, for example. A corresponding system is also provided.