Systems and methods are provided for enhancing object feature visibility for overhead imaging. In one embodiment, a computing system can obtain information associated with one or more locations of an imaging platform and one or more locations of a solar source. The system can determine one or more positional ranges of the imaging platform relative to the solar source based, at least in part, on such information. The positional ranges can be indicative of positions at which the imaging platform is to obtain image frames depicting at least a portion of a target object. The system can send, to the imaging platform, a set of data indicative of the positional ranges and can receive, from the imaging platform, a set of data indicative of the image frames depicting at least a portion of the target object. The image frames being captured based, at least in part, on the positional ranges.

A method for tracking a moving target based on an optical flow method, including, providing video images, and implementing pre-processing of the images to generate pre-processed images; implementing edge-detection of the pre-processed images and using an optical flow method to extract target information from the pre-processed images, and on the basis of a combination of the edge-detection information and the extracted target information, generating a complete moving target; using an optical flow method to perform estimation analysis of the moving target and using a forward-backward error algorithm based on feature point trace to eliminate light-generated false matching points; and creating a template image and implementing template image matching to track the moving target. The method and system for tracking a moving target based on an optical flow method have the advantages of accurate and complete extraction and the ability to implement stable tracking over a long period of time.

Visibility of a license plate and color reproducibility of a vehicle body are improved in a monitoring camera. A vehicle body area detection unit detects a vehicle body area of a vehicle from an image signal. A license plate area detection unit detects a license plate area of the vehicle from the image signal. A vehicle body area image processing unit performs processing of the image signal corresponding to the detected vehicle body area. A license plate area image processing unit performs processing different from the processing of the image signal corresponding to the vehicle body area on the image signal corresponding to the detected license plate area. A synthesis unit synthesizes the processed image signal corresponding to the vehicle body area and the processed image signal corresponding to the license plate area.

An image recognition device, an image recognition method and an image recognition unit are capable of performing touch recognition high in accuracy. The image recognition device includes a measurement point determination section adapted to determine a fingertip from an image obtained by a camera, a pattern display section adapted to make a projector display a first pattern having a first linear pattern varying in luminance with a first pitch along a direction parallel to an epipolar line passing through the fingertip, and a second linear pattern varying in luminance with a second pitch along a direction parallel to the epipolar line, and a position detection section adapted to perform touch recognition based on a variation of the first pattern from the image including the first pattern.

A terminal control method executed by a computer, includes detecting that an image of a reference object is included in a captured image; and sending identification information that identifies the reference object or content associated with the reference object, position information that indicates a position of the reference object or the content in the captured image, and the captured image to an information processing apparatus that is configured to combine a content associated with received identification information, with a received captured image, based on received position information.

A method for tracking a moving target based on an optical flow method, including, providing video images, and implementing pre-processing of the images to generate pre-processed images; implementing edge-detection of the pre-processed images and using an optical flow method to extract target information from the pre-processed images, and on the basis of a combination of the edge-detection information and the extracted target information, generating a complete moving target; using an optical flow method to perform estimation analysis of the moving target and using a forward-backward error algorithm based on feature point trace to eliminate light-generated false matching points; and creating a template image and implementing template image matching to track the moving target. The method and system for tracking a moving target based on an optical flow method have the advantages of accurate and complete extraction and the ability to implement stable tracking over a long period of time.

An eyeball tracking method and apparatus, and a device. The method comprises: acquiring a facial grey-scale image set to be detected (101); judging whether the contour of an eyeball iris is determined in an N-th frame facial grey-scale image in the facial grey-scale image set to be detected (102); if not, detecting an eyeball pupil in the N-th frame facial grey-scale image, and determining the central position of the eyeball pupil in the N-th frame facial grey-scale image (103); in the N-th frame facial grey-scale image, taking the central position of the eyeball pupil as a centre to determine a grey-scale image region corresponding to an eyeball window (104); and according to the grey-scale image region corresponding to the eyeball window, determining the contour of the eyeball iris in the N-th frame facial grey-scale image (105). By judging that the contour of an eyeball iris is not determined in a facial grey-scale image, the tracking of the contour of the eyeball iris can be automatically adjusted, and an eyeball pupil is positioned again. By means of the present invention, the accuracy rate of eyeball tracking is improved, and an eyeball can be automatically identified to detect the central position of an eyeball pupil.

Automatic nuclear segmentation. In an embodiment, a plurality of superpixels are determined in a digital image. For each of the superpixels, any superpixels located within a search radius from the superpixel are identified, and, for each unique local combination between the superpixel and any identified superpixels located within the search radius from the superpixel, a local score for the local combination is determined. One of a plurality of global sets of local combinations with an optimum global score is identified based on the determined local scores.

Systems and methods are provided for enhancing object feature visibility for overhead imaging. In one embodiment, a computing system can obtain information associated with one or more locations of an imaging platform and one or more locations of a solar source. The system can determine one or more positional ranges of the imaging platform relative to the solar source based, at least in part, on such information. The positional ranges can be indicative of positions at which the imaging platform is to obtain image frames depicting at least a portion of a target object. The system can send, to the imaging platform, a set of data indicative of the positional ranges and can receive, from the imaging platform, a set of data indicative of the image frames depicting at least a portion of the target object. The image frames being captured based, at least in part, on the positional ranges.

First image data captured by a first image pickup apparatus and second image data captured by a second image pickup apparatus are stored in storing means. Thus, it is possible to correlate images with each other by using identification information of a user or the image pickup apparatus and identification information of an image capturing time, an image capturing position, or an image pickup target (event). Further, the correlated image data is edited on the basis of editing structure data, thereby generating album image data.