Abstract: An object detection device including at least one image capture element can capture image data in a field of view and detect types of objects located in that region. Information such as a direction of travel or speed of the object may be used to determine a relative position of the object of interest, for example relative to the object detection device or a target object. The data from multiple devices for a region can be aggregated such that objects can be tracked as they move though the region. Information about the relative position of the object of interest can be used to trigger alerts to users in the area.

Abstract: An object detection device including at least one image capture element can capture image data in a field of view and detect types of objects located in that region. Information such as a direction of travel or speed of the object may be used to determine a relative position of the object of interest, for example relative to the object detection device or a target object. The data from multiple devices for a region can be aggregated such that objects can be tracked as they move though the region. Information about the relative position of the object of interest can be used to trigger alerts to users in the area.

Abstract: An intelligent content display system includes an electronic display and one or more image sensors having a field of view. The image sensors generate image data representing a scene within the field of view. One or more conditions can be determined from the image data, such as types of objects present in the scene, including people, vehicles, among others. Such detected conditions may be used to determine what content to display on the electronic display in order to optimize the display. A model may be trained using training data to make such as a determination based on the present detected condition. The training data may include historical data which may include various performance measure values and the associated display content associated with certain types of detected objects.

Abstract: An object detection system can utilize multiple detection devices, each including at least one image capture element that can capture image data for a region of interest and detect types of objects located in that region. Information such as the coordinates of the objects and descriptors for the objects can be transmitted, along with timestamp data, in order to allow those objects to be counted, tracked, or otherwise monitored by a separate system without transmitting the image data or potentially sensitive data regarding the objects. The data from multiple devices for the region can be aggregated such that objects can be tracked as the objects switch between different fields of view of different devices, based on the location and descriptor data. Information about the presence, location, or movement of certain types of actions can be used to trigger specific actions, such as to allocate resources or generated alarms based thereon.

Abstract: An object detection device including at least one image capture element can capture image data for a region of interest and detect types of objects located in that region. Information such as the coordinates of the objects and descriptors for the objects can be transmitted, along with timestamp data, in order to allow those objects to be counted, tracked, or otherwise monitored by a separate system without transmitting the image data or potentially sensitive data regarding the objects. The data from multiple devices for the region can be aggregated such that objects can be tracked as the objects switch between different fields of view of different devices, based on the location and descriptor data. Information about the presence, location, or movement of certain types of action can then be used to trigger specific actions, such as to allocate resources or generated alarms based thereon.

Abstract: An unmanned aerial vehicle (UAV) can include one or more cameras for capturing image data within a field of view that depends in part upon the location and orientation of the UAV. At least a portion of the image data can be processed on the UAV to locate objects of interest, such as people or cars, and use that information to determine where to fly the drone in order to capture higher quality image data of those or other such objects. Once identified, the objects of interest can be counted, and the density, movement, location, and behavior of those objects identified. This can help to determine occurrences such as traffic congestion or unusual patterns of pedestrian movement, as well as to locate persons, fires, or other such objects. The data can also be analyzed by a remote system or service that has additional resources to provide more accurate results.

Abstract: An unmanned aerial vehicle (UAV) can include one or more cameras for capturing image data within a field of view that depends in part upon the location and orientation of the UAV. At least a portion of the image data can be processed on the UAV to locate objects of interest, such as people or cars, and use that information to determine where to fly the drone in order to capture higher quality image data of those or other such objects. Once identified, the objects of interest can be counted, and the density, movement, location, and behavior of those objects identified. This can help to determine occurrences such as traffic congestion or unusual patterns of pedestrian movement, as well as to locate persons, fires, or other such objects. The data can also be analyzed by a remote system or service that has additional resources to provide more accurate results.

Abstract: An unmanned aerial vehicle (UAV) can include one or more cameras for capturing image data within a field of view that depends in part upon the location and orientation of the UAV. At least a portion of the image data can be processed on the UAV to locate objects of interest, such as people or cars, and use that information to determine where to fly the drone in order to capture higher quality image data of those or other such objects. Once identified, the objects of interest can be counted, and the density, movement, location, and behavior of those objects identified. This can help to determine occurrences such as traffic congestion or unusual patterns of pedestrian movement, as well as to locate persons, fires, or other such objects. The data can also be analyzed by a remote system or service that has additional resources to provide more accurate results.