45 results about "Active camera" patented technology

If an active smart node detects that an object leaves a center region of a FOV for a boundary region, the active smart node predicts a possible path of the object. When the object gets out of the FOV, the active smart node predicts the object appears in a FOV of another smart node according to the possible path and a spatial relation between cameras. The active smart node notifies another smart node to become a semi-active smart node which determines an image characteristic similarity between the object and a new object and returns to the active smart node if a condition is satisfied. The active smart node compares the returned characteristic similarity, an object discovery time at the semi-active smart node, and a distance between the active smart node and the semi-active smart node to calculate possibility.

Systems and methods for high dynamic range imaging using array cameras in accordance with embodiments of the invention are disclosed. In one embodiment of the invention, a method of generating a high dynamic range image using an array camera includes defining at least two subsets of active cameras, determining image capture settings for each subset of active cameras, where the image capture settings include at least two exposure settings, configuring the active cameras using the determined image capture settings for each subset, capturing image data using the active cameras, synthesizing an image for each of the at least two subset of active cameras using the captured image data, and generating a high dynamic range image using the synthesized images.

Systems and methods for reducing motion blur in images or video in ultra low light with array cameras in accordance with embodiments of the invention are disclosed. In one embodiment, a method for synthesizing an image from multiple images captured using an array camera includes capturing image data using active cameras within an array camera, where the active cameras are configured to capture image data and the image data includes pixel brightness values that form alternate view images captured from different viewpoints, determining sets of corresponding pixels in the alternate view images where each pixel in a set of corresponding pixels is chosen from a different alternate view image, summing the pixel brightness values for corresponding pixels to create pixel brightness sums for pixel locations in an output image, and synthesizing an output image from the viewpoint of the output image using the pixel brightness sums.

A system and method for assuring a high resolution image of an object, such as the face of a person, passing through a targeted space are provided. Both stationary and active or pan-tilt-zoom cameras are utilized. The at least one stationary camera acts as a trigger point such that when a person passes through a predefined targeted area of the at least one stationary camera, the system is triggered for object imaging and tracking. Upon the occurrence of a triggering event in the system, the system predicts the motion and position of the person. Based on this predicted position of the person, an active camera that is capable of obtaining an image of the predicted position is selected and may be controlled to focus its image capture area on the predicted position of the person. After the active camera control and image capture processes, the system evaluates the quality of the captured face images and reports the result to the security agents and interacts with the user.

A system and method for assuring a high resolution image of an object, such as the face of a person, passing through a targeted space are provided. Both stationary and active or pan-tilt-zoom cameras are utilized. The at least one stationary camera acts as a trigger point such that when a person passes through a predefined targeted area of the at least one stationary camera, the system is triggered for object imaging and tracking. Upon the occurrence of a triggering event in the system, the system predicts the motion and position of the person. Based on this predicted position of the person, an active camera that is capable of obtaining an image of the predicted position is selected and may be controlled to focus its image capture area on the predicted position of the person. After the active camera control and image capture processes, the system evaluates the quality of the captured face images and reports the result to the security agents and interacts with the user.

An eye tracker includes at least one illuminator for illuminating an eye, at least two cameras for imaging the eye, and a controller. The configuration of the reference illuminator(s) and cameras is such that, at least one camera is coaxial with a reference illuminator and at least one camera is non-coaxial with a reference illuminator. The controller is adapted to select one of the cameras to be active to maximize an image quality metric and avoid obscuring objects. The eye tracker is operable in a dual-camera mode to improve accuracy. A method and computer-program product for selecting a combination of an active reference illuminator from a number of reference illuminators, and an active camera from a plurality of cameras are provided.

An outer body of ball shell type has an opening. A camera is located in the outer body and receives an image from outside of the outer body through the opening. A camera support unit is located in the outer body and rotationally supports the camera along a first axis and a second axis mutually crossed at a center of the outer body. A first camera actuator is located in the outer body and rotationally actuates the camera around the first axis. A second camera actuator is located in the outer body and rotationally actuates the camera around the second axis.

If an active smart node detects that an object leaves a center region of a FOV for a boundary region, the active smart node predicts a possible path of the object. When the object gets out of the FOV, the active smart node predicts the object appears in a FOV of another smart node according to the possible path and a spatial relation between cameras. The active smart node notifies another smart node to become a semi-active smart node which determines an image characteristic similarity between the object and a new object and returns to the active smart node if a condition is satisfied. The active smart node compares the returned characteristic similarity, an object discovery time at the semi-active smart node, and a distance between the active smart node and the semi-active smart node to calculate possibility.

An electronic device (10) includes camera circuitry (82) for carrying out a camera related operation, the camera circuitry including a camera lens (30) that is at least partially covered by a visual indicator element. The visual indicator element (40) is substantially opaque when the camera circuitry is in a first state (e.g., an 'off' state) and the visual indicator element is substantially transparent when the camera circuitry is in a second state (e.g., an 'on' state). Optionally, an audible and / or visual indication mechanism may also be output to the user when the camera circuitry is activated.

The present invention discloses a complex water area target tracking method based on an AIS (automatic identification system) and an active camera. The method comprises the following steps that: 1) an observation area is divided into n cells, each camera of an active camera group is separately calibrated according to each cell, so that the intrinsic parameters and extrinsic parameters of the cameras are obtained; (2) the AIS device is utilized to calibrate the cells in advance, and calibration information is stored, after a target object enters a relevant cell, the cell where the target object is located is determined according to position information returned by the AIS; (3) the active camera group is made to rapidly move to the area of the cell where the target is located, wherein the active camera group contains m active cameras; and (4) the clear video image of the target object is shot, and the target object is tracked according to an tracking algorithm. According to the method of the invention, a new image pickup idea is provided; and the cell division mode is adopted, and the AIS system and the cells are combined to determine the position and heading of the target object.

The present invention relates to a functional optical coherent imaging (fOCI) platform comprising at least one active camera unit (ACU) comprising a coherent and / or a partially coherent light source, and means for spectral filtering and imaging a selected body area of interest; an image processing unit (IPU) for pre-processing data received from an ACU; at least one stimulation unit (STU) transmitting a stimulation to a subject; at least one body function reference measurement unit (BFMU); a central clock and processing unit (CCU), with interconnections to the ACU, the IPU, the STU, for collecting pre-processed data from the IPU, stimuli from the STU body function reference data from the BFMU in a synchronized manner; a post-processing unit (statistical analysis unit, SAU); and an operator interface (HOD. Further the invention relates to a process for acquiring stimuli activated subject data comprising the steps of aligning a body function unit at a subject and monitoring pre-selected body function; selecting a stimulus or stimuli; imaging a body area of interest; exerting one or a series of stimuli on the subject; imaging the body area of interest synchronous with said stimuli and the preselected body functions; and transferring said synchronized image, stimuli and body function data to a statistical analysis unit (SAU) and performing calculations to generate results pertaining to body functions.

The invention discloses an active vision human face tracking method and tracking system of a robot; the tracking method comprises the steps that: (1) the mobile robot acquires an environment information image and detects a human face target through an active camera; and (2) after the human face target is detected, the robot tracks the human face target, and maintains the human face target in the center of the image through the active camera and the movement of the robot. The tracking system comprises the active camera, an image tracking module, a movement tracking module, a hierarchy buffer module and a state feedback module. The invention realizes the automatic human face detection and tracking by the robot, overcomes the limitation of a smaller image vision angle and establishes a perception-movement ring of the mobile robot based on active vision by combining the image tracking with the movement tracking, so that the movement scope for human face tracking is expanded to 360 degrees, the all-sided expansion of the tracking scope is ensured. A two-layer buffer region ensures the tracking continuity, so that the human face target is always maintained in the center of the image.