Abstract: This application is directed to a doorbell camera for illuminating and capturing scenes. The doorbell camera includes at least a subset of processors for operating a camera module, an image sensor having a field of view of a scene and configured to capture video of a portion of the scene, one or more infrared (IR) illuminators for providing illumination, a waterproof button assembly, and a microphone and a speaker for enabling a real-time conversation between a visitor located at the doorbell camera and a user of a remote client device. The waterproof button assembly is configured to receive a user press on a button top, block water from entering the electronic device, and display a visual pattern uniformly at a peripheral region of the button assembly using LEDs and light guide component that are disposed under the button top.

Abstract: A method and system for optically detecting a user. A sequence of patterns of radiation reflected from an object in a room may be captured by a device. The patterns of radiation may be infrared radiation emitted from the device. A sequence of variations between the captured sequence of patterns of radiation and the emitted sequence of patterns of radiation may be determined and object characteristics of an object may be determined based upon the sequence of variations. The object characteristics may be a sequence of dimensions of the object and a sequence of locations of the object. The method may determine the first is a user based upon the determined object characteristics and a room profile. The room profile may include a plurality of object characteristics of one or more objects in the room.

Abstract: This application discloses a method implemented by an electronic device to detect a signature event (e.g., a baby cry event) associated with an audio feature (e.g., baby sound). The electronic device obtains a classifier model from a remote server. The classifier model is determined according to predetermined capabilities of the electronic device and ambient sound characteristics of the electronic device, and distinguishes the audio feature from a plurality of alternative features and ambient noises. When the electronic device obtains audio data, it splits the audio data to a plurality of sound components each associated with a respective frequency or frequency band and including a series of time windows. The electronic device further extracts a feature vector from the sound components, classifies the extracted feature vector to obtain a probability value according to the classifier model, and detects the signature event based on the probability value.

Abstract: Systems and methods for exchanging a data stream of information that varies over time using a message format. The message format includes a version field that indicates a version of a structure of the message format. The message format also includes one or more resources fields that each identifies a resource to be imported into the data stream exchanging the data stream. Moreover, the message format includes one or more records that represent time-variant data samples being exchanged in the message. Furthermore, the message format includes one or more descriptor fields, wherein each descriptor field corresponds to at least one respective record of the one or more records and contains metadata describing data contained within the at least one record.

Abstract: A system and method for the use of sensors and processors of existing, distributed systems, operating individually or in cooperation with other systems, networks or cloud-based services to enhance the detection and classification of sound events in an environment (e.g., a home), while having low computational complexity. The system and method provides functions where the most relevant features that help in discriminating sounds are extracted from an audio signal and then classified depending on whether the extracted features correspond to a sound event that should result in a communication to a user. Threshold values and other variables can be determined by training on audio signals of known sounds in defined environments, and implemented to distinguish human and pet sounds from other sounds, and compensate for variations in the magnitude of the audio signal, different sizes and reverberation characteristics of the environment, and variations in microphone responses.

Abstract: Hazard detection systems and methods according to embodiments described herein are operative to enable a user to interface with the hazard detection system by performing a touchless gesture. The touchless gesture can be performed in a vicinity of the hazard detection system without requiring physical access to the hazard detection system. This enables the user to interact with the hazard detection system even if it is out of reach. The hazard detection system can detect gestures and perform an appropriate action responsive to the detected gesture. In one embodiment, the hazard detection system can silence its audible alarm or pre-emptively turn off its audible alarm in response to a detected gesture. Gestures can be detected by processing sensor data to determine whether periodic shapes are detected.

Abstract: A process estimates height and tilt of a camera having an image sensor array and IR illuminators. The process identifies multiple distinct subsets of the illuminators. For multiple heights and tilts, the process constructs dictionary entries that correspond to the camera having the height and tilt above a floor. Each entry includes light intensity values for pixels in images corresponding to activating each of the subsets of illuminators. For each of the subsets, the process receives an image of a scene captured while the subset is emitting light and the other illuminators are not. The process uses the captured images to identify a floor region corresponding to a floor in the scene. The process forms a vector including pixels from the captured images in the identified floor region and estimates the height and tilt of the camera by comparing the vector to the dictionary entries.

Abstract: A system and method for the use of sensors and processors of existing, distributed systems, operating individually or in cooperation with other systems, networks or cloud-based services to enhance the detection and classification of sound events in an environment (e.g., a home), while having low computational complexity. The system and method provides functions where the most relevant features that help in discriminating sounds are extracted from an audio signal and then classified depending on whether the extracted features correspond to a sound event that should result in a communication to a user. Threshold values and other variables can be determined by training on audio signals of known sounds in defined environments, and implemented to distinguish human and pet sounds from other sounds, and compensate for variations in the magnitude of the audio signal, different sizes and reverberation characteristics of the environment, and variations in microphone responses.

Abstract: A system and method for automatic path light control based on a detected size and classification of motion around the device using passive infrared (PIR) sensor technologies and distributed classification algorithms, and on detected light levels in and around the path area using ambient light sensor (ALS) technologies. By using such sensor data, the path light does not need to be maintained at a fixed value, which may be inadequate or inefficient at times, nor require constant user adjustments. Implementations of the disclosed subject matter enable automatic path light control that can be dynamic and automatically adjusted to fit the environment, the current user characteristics and the current user movements through the environment.

Abstract: A camera system includes non-volatile memory, a lens, an image sensor to capture images of a scene within view of the lens, an IR illuminator, and a processing system. The processing system transitions the camera system from day mode to night mode when the scene is dark, and in the night mode, two operations are performed. The first operation uses the IR illuminator, the image sensor, and the memory to capture a first IR image or video of the scene and store the first IR image or video in the non-volatile memory. The second operation uses the IR illuminator, the image sensor, and the memory to identify a specular surface in the scene. This includes capturing a second IR image or video, identifying a first region of low intensity pixels, and storing, in the non-volatile memory, position parameters of the first region and designating the first region as specular.

Abstract: Systems and techniques are provided for dynamic volume adjustment. A signal including a detected distance to a person may be received from a proximity sensor of a smart home environment. A volume adjustment for a speaker of the smart home environment may be generated based on the detected distance to the person and a sound level associated with the detected distance to the person. The volume of the speaker may be adjusted based on the volume adjustment. A signal from a sensor of the smart home environment indicating that the sensor has been tripped may be received. The proximity sensor may be triggered based on the received signal indicating the sensor has been tripped to detect a distance to the person to generate the detected distance. An alarm may be sounded through the speaker.

Abstract: A method includes capturing data with a plurality of network connected sensors installed in or around a premises, storing at least a sampling of the data in an electronic storage device, analyzing the stored data with a processor to automatically identify one or more types of trends or patterns, creating, based on the analysis, a zone definition for a first zone that corresponds to an area of the premises from which data was captured by one or more sensors selected from among the plurality of sensors, and configuring at least one system operating in or around the premises automatically based on the first zone definition.

Abstract: A camera system includes memory, image sensors, illuminators, and a processor. The processor operates the illuminators and the image sensors in a first mode to capture a two-dimensional image of the scene using light transmitted by the illuminators and reflected from the scene. The processor operates in a second mode to capture a plurality of images of the scene, including capturing a first image of the scene while one or more of the illuminators are activated and capturing a second image of the scene is while none of the illuminators are activated. The images are transmitted to a remote cloud computing system. The remote system constructs a light intensity map for the scene using the first and second images, and identifies a first region in the light intensity map as a glass surface when the light intensity values for the first region are below a threshold value corresponding to glass.

Abstract: In an implementation of the disclosed subject matter, a device may emit a first emission sequence of infrared radiation at a subject, and capture a first reflected sequence of infrared radiation reflected from the subject. The first emission sequence may be compared to the first reflected sequence, and, based on the comparison, a sequence of variations may be determined. The sequence of variations may be compared to signal pattern stored in a sleep profile for the subject. The subject may be determined to have exhibited sleep behavior based on the comparison of the sequence of variations to the signal pattern stored in the sleep profile. In response to determining the subject has exhibited sleep behavior, the device may capture a second reflected sequence of radiation reflected from the subject. A breathing rate of the subject and/or a heart rate of the subject may be determined based on the second reflected sequence.

Abstract: A process reduces false positive security alerts. The process is performed at a computing device having one or more processors, and memory storing one or more programs configured for execution by the one or more processors. The process computes a depth map for a scene monitored by a video camera using a plurality of IR images captured by the video camera and uses the depth map to identify a first region within the scene having historically above average false positive detected motion events. In some instances, the first region is a ceiling, a window, or a television. The process monitors a video stream provided by the video camera to identify motion events, excluding the first region, and generates a motion alert when there is detected motion in the scene outside of the first region and the detected motion satisfies threshold criteria.

Abstract: A process identifies large planar surfaces in scenes. The process receives captured IR images of a scene taken by a 2-dimensional array of image sensors of a camera system. Each IR image is captured when a distinct subset of IR illuminators of the camera system is illuminated. The process constructs a depth map of a scene using IR images and uses the depth map to compute a binary depth edge map for the scene. The binary depth edge map identifies which points in the depth map comprise depth discontinuities. The process identifies contiguous components based on the binary depth edge map and determines that a first component of the contiguous components represents a large planar surface in the scene by: fitting a plane to points in the first component; determining the orientation of the plane; and determining that the plane fitting residual error is less than a predefined threshold.

Abstract: Hazard detection systems and methods according to embodiments described herein are operative to enable a user to interface with the hazard detection system by performing a touchless gesture. The touchless gesture can be performed in a vicinity of the hazard detection system without requiring physical access to the hazard detection system. This enables the user to interact with the hazard detection system even if it is out of reach. The hazard detection system can detect gestures and perform an appropriate action responsive to the detected gesture. In one embodiment, the hazard detection system can silence its audible alarm or pre-emptively turn off its audible alarm in response to a detected gesture. Gestures can be detected by processing sensor data to determine whether periodic shapes are detected.

Abstract: A camera system includes memory, a lens assembly arranged to direct light from a scene onto an image sensing element, an image sensing element configured to receive light from the scene via the lens assembly, at least one infrared illuminator configured to transmit infrared light, and a processor, coupled to the image sensing element and the illuminators. The processor is configured to operate the illuminators and the image sensing element in a first mode whereby infrared light transmitted by the illuminators and reflected from the scene is used to generate a two-dimensional image of the scene. The processor is also configured to operate the illuminators and the image sensing element in a second mode whereby infrared light transmitted by the illuminators and reflected from the scene is used to detect a first region, located within the scene, having a specific material.

Abstract: A camera system includes memory, a lens assembly to direct light from a scene onto an image sensing element, an image sensing element configured to receive light from the scene via the lens assembly, at least one infrared illuminator configured to transmit infrared light, and a processor, coupled to the image sensing element and the at least one infrared illuminator. The processor is configured to operate the illuminators and the image sensing element in a first mode whereby infrared light transmitted by the illuminators and reflected from the scene is used to generate a two-dimensional image of the scene. The processor is also configured to operate the illuminators and the image sensing element in a second mode whereby infrared light transmitted by the illuminators and reflected from the scene is used to identify a planar surface in the scene.

Abstract: A process classifies objects in a scene. The process receives a captured IR image of a scene taken by a 2-dimensional image sensor array of a camera system while one or more IR illuminators of the camera system are emitting IR light, thereby forming an IR intensity map of the scene with a respective intensity value determined for each pixel of the IR image. The process uses the IR intensity map to identify a plurality of pixels whose corresponding intensity values are within a predefined intensity range, and clusters the identified plurality of pixels into one or more regions that are substantially contiguous. The process determines that a first region of the one or more regions corresponds to a specific material based, at least in part, on the intensity values of the pixels in the first region. The process then stores information in the memory that identifies the first region.