Abstract: A low-cost, low-power, stand-alone sensor platform having a visible-range camera sensor, a thermopile array, a microphone, a motion sensor, and a microprocessor that is configured to perform occupancy detection and counting while preserving the privacy of occupants. The platform is programmed to extract shape/texture from images in spatial domain; motion from video in time domain; and audio features in frequency domain. Embedded binarized neural networks are used for efficient object of interest detection. The platform is also programmed with advanced fusion algorithms for multiple sensor modalities addressing dependent sensor observations. The platform may be deployed for (i) residential use in detecting occupants for autonomously controlling building systems, such as HVAC and lighting systems, to provide energy savings, (ii) security and surveillance, such as to detect loitering and surveil places of interest, (iii) analyzing customer behavior and flows, (iv) identifying high performing stores by retailers.

Abstract: A low-cost, low-power, stand-alone sensor platform having a visible-range camera sensor, a thermopile array, a microphone, a motion sensor, and a microprocessor that is configured to perform occupancy detection and counting while preserving the privacy of occupants. The platform is programmed to extract shape/texture from images in spatial domain; motion from video in time domain; and audio features in frequency domain. Embedded binarized neural networks are used for efficient object of interest detection. The platform is also programmed with advanced fusion algorithms for multiple sensor modalities addressing dependent sensor observations. The platform may be deployed for (i) residential use in detecting occupants for autonomously controlling building systems, such as HVAC and lighting systems, to provide energy savings, (ii) security and surveillance, such as to detect loitering and surveil places of interest, (iii) analyzing customer behavior and flows, (iv) identifying high performing stores by retailers.

Abstract: There is set forth herein a system including a camera device. In one embodiment the system is operative to perform image processing for detection of an event involving a human subject. There is set forth herein in one embodiment, a camera equipped system employed for fall detection.

Abstract: There is set forth herein a system including a camera device. In one embodiment the system is operative to perform image processing for detection of an event involving a human subject. There is set forth herein in one embodiment, a camera equipped system employed for fall detection.

Abstract: There is set forth herein a system including a camera device. In one embodiment the system is operative to perform image processing for detection of an event involving a human subject. There is set forth herein in one embodiment, a camera equipped system employed for fall detection.

Abstract: A system and method for monitoring events includes defining alert events based on primitive event types in an environment monitored by monitoring devices. Alert parameters are set for each alert event, and alert events are combined to create a composite alert event based on a plurality of alert events. A plurality of engines is monitored to determine if multiple events comprising the composite alert event have occurred.

Abstract: Techniques for tracking entities using a single overhead camera are provided. A foreground region is detected in a video frame of the single overhead camera corresponding to one or more entities. It is determined if the foreground region is associated with an existing tracker. It is determined whether the detected foreground region is the result of at least one of a merger of two or more smaller foreground regions having corresponding existing trackers and a split of a larger foreground region having a corresponding existing tracker when the detected foreground region is not associated with an existing tracker. The detected foreground region is tracked via at least one existing tracker when the foreground region is associated with an existing tracker or the foreground region is the result of at least one of a merger and a split.

Abstract: A system and method for monitoring events includes defining alert events based on primitive event types in an environment monitored by monitoring devices. Alert parameters are set for each alert event, and alert events are combined to create a composite alert event based on a plurality of alert events. A plurality of engines is monitored to determine if multiple events comprising the composite alert event have occurred.

Abstract: A method for monitoring events includes defining alert events based on primitive event types in an environment monitored by monitoring devices. Alert parameters are set for each alert event, and alert events are combined to create a composite alert event based on a plurality of alert events. A plurality of engines is monitored to determine if multiple events comprising the composite alert event have occurred.

Abstract: Techniques for tracking entities using a single overhead camera are provided. A foreground region is detected in a video frame of the single overhead camera corresponding to one or more entities. It is determined if the foreground region is associated with an existing tracker. It is determined whether the detected foreground region is the result of at least one of a merger of two or more smaller foreground regions having corresponding existing trackers and a split of a larger foreground region having a corresponding existing tracker when the detected foreground region is not associated with an existing tracker. The detected foreground region is tracked via at least one existing tracker when the foreground region is associated with an existing tracker or the foreground region is the result of at least one of a merger and a split.

Abstract: Techniques for tracking entities using a single overhead camera are provided. A foreground region is detected in a video frame of the single overhead camera corresponding to one or more entities. It is determined if the foreground region is associated with an existing tracker. It is determined whether the detected foreground region is the result of at least one of a merger of two or more smaller foreground regions having corresponding existing trackers and a split of a larger foreground region having a corresponding existing tracker when the detected foreground region is not associated with an existing tracker. The detected foreground region is tracked via at least one existing tracker when the foreground region is associated with an existing tracker or the foreground region is the result of at least one of a merger and a split.

Abstract: A system and method for monitoring events includes defining alert events based on primitive event types in an environment monitored by monitoring devices. Alert parameters are set for each alert event, and alert events are combined to create a composite alert event based on a plurality of alert events. A plurality of engines is monitored to determine if multiple events comprising the composite alert event have occurred.

Abstract: Techniques for tracking entities using a single overhead camera are provided. A foreground region is detected in a video frame of the single overhead camera corresponding to one or more entities. It is determined if the foreground region is associated with an existing tracker. It is determined whether the detected foreground region is the result of at least one of a merger of two or more smaller foreground regions having corresponding existing trackers and a split of a larger foreground region having a corresponding existing tracker when the detected foreground region is not associated with an existing tracker. The detected foreground region is tracked via at least one existing tracker when the foreground region is associated with an existing tracker or the foreground region is the result of at least one of a merger and a split.