Avigilon Corporation

Motorola Solutions, Inc.

Pathai, Inc.

Bo Yang Yu

Pietro Russo

Kevin Piette

Yanyan Hu

Moussa Doumbouya

Mahesh Saptharishi

Peter L Venetianer

Peter Anderholm

Justin Lee

Hsiou-Yuan Liu

Bikram Yonjan

Yibo Zhang

Alias capture to support searching for an object-of-interest is disclosed. A method includes capturing, using a camera with a defined field of view, video image frames that include a moving object-of-interest. The method also includes tracking the object-of-interest over a period of time starting when the object-of-interest enters the field of view and ending when the object-of-interest exits the field of view. The method also includes detecting, at a point in time in-between the start and end of the period of time of the tracking, a threshold exceeding change in an appearance of the object-of-interest. The method also includes creating, before the end of the period of time of the tracking, a new object profile for the object-of-interest in response to the detecting of the threshold exceeding change.

Alias capture to support searching for an object-of-interest

Diffraction-based imaging systems are described. Aspects of the technology relate to imaging systems having one or more sensors inclined at angles with respect to a sample plane. In some cases, multiple sensors may be used that are, or are not, inclined at angles. The imaging systems may have no optical lenses and are capable of reconstructing microscopic images of large sample areas from diffraction patterns recorded by the one or more sensors. Some embodiments may reduce mechanical complexity of a diffraction-based imaging system. A diffractive imaging system comprises a light source, a sample support configured to hold a sample along a first plane, and a first sensor comprising a plurality of pixels disposed in a second plane that is tilted at an inclined angle relative to the first plane. The first sensor is arranged to record diffraction images of the light source from the sample.

Imaging systems with angled sensors and related methods

Methods, systems, and techniques for monitoring an object-of-interest within a region involve receiving at least data from two sources monitoring a region and correlating that data to determine that an object-of-interest depicted or represented in data from one of the sources is the same object-of-interest depicted or represented in data from the other source. Metadata identifying that the object-of-interest from the two sources is the same object-of-interest is then stored for later use in, for example, object tracking.

Sensor fusion for monitoring an object-of-interest in a region

Methods, systems, and techniques for classifying and/or detecting objects using visible and invisible light images. A visible light image and an invisible light image are received at a convolutional neural network (CNN). The visible light image depicts a region-of-interest imaged using visible light. The invisible light image depicts at least a portion of the region-of-interest imaged using invisible light, and at least one of the images depicts an object-of-interest within the portion of the region-of-interest shared between the images. The CNN then classifies and/or detects the object-of-interest using the images. The CNN may be trained to perform this classification and/or detection using pairs of visible and invisible light training images.

Method and system for object classification using visible and invisible light images

A computer-implemented method comprises detecting, with a presence detector such as a radar device, a presence of a person at a location such as an ATM vestibule. In response thereto, a timer is initiated. After initiating the timer, a portal sensor is used to detect a change in a status of a portal permitting access to the location. In response thereto, the timer is adjusted (for example the timer is reset). Thus, multiple consecutive normal usages of the vestibule do not unnecessarily trigger an alarm.

Presence detection and uses thereof

A system is provided, including: a radar sensor configured to transmit and receive a radar signal from a person; a depth camera configured to receive a depth image of the person; one or more processors communicative with memory having stored thereon computer program code configured when executed by the one or more processors to cause the one or more processors to perform a method comprising: detect the person; determine depth information relating to the person using the depth image; determine a correlation between the depth information of the person and the radar signal received from the person; and in response to the correlation not within a range of expected values, generating an alert. The depth information may be a volume or surface area of the person.

Human profile and anomaly detection

An electronic movement-controlled apparatus that includes a camera and a movable arm is disclosed. The movable arm has both a stationary end and a movable end with the camera being attached to the movable end so as to be movable therewith. The stationary end is configured to be coupled to a rigid support structure. The movable arm includes a plurality of arm segments connected in series to form the movable arm. The arm segments are configured to have cooperating segment regions in terms of each of the arm segments being compressible and expandable in unison to move the movable end and effect a pan and tilt movement of the camera.

Camera on movable arm

A surveillance drone is disclosed. The surveillance drone includes a gas-filled container and propellers for aerial mobility. The surveillance drone also includes an electronic surveillance sensing device positioned below the gas-filled container. The gas-filled container may be filled with a lighter than air gas such as, for example, helium.

Surveillance drone including gas-filled container and propellers for aerial mobility

A computer-implemented method for detecting a person in a room using a sensor, such as a radar sensor or depth cameras is provided. The method can be used to detect sleeping persons in a publically accessible location to prevent loitering. Furthermore, the method can be used to identify which rooms amongst a plurality of rooms are occupied, for example changing rooms.

Growing community of inventors

Winchester, MA, United States of America

Bo Yang Yu