703 results about "Image evaluation" patented technology

A motion capture apparatus includes: generating means; predicting means; projecting means; evaluating means; and estimating means. The generating means generates a kinematics model having joints connected to one another. The predicting means hierarchically calculates predicted positions at a current time of the joints of the objective person, and predicts three-dimensional positions and postures of the joints and the limbs. The projecting means projects the three-dimensional positions and postures of the joints and the limbs of the objective person on a two-dimensional image plane, the three-dimensional positions and the postures being predicted by predicting means. The evaluating means evaluates reliability about projection positions projected by the projecting means based on the observation image of the objective person. The estimating means estimates the three-dimensional positions and postures of the joints and the limbs of the objective person at the current time based on an evaluation result about the reliability.

An image focus assessment method is provided that works reliably for images of a variety of relatively dissimilar workpieces or workpiece features. The focus assessment method is based on analysis of a single image (without the benefit of comparison to other images). The robustness of the focus assessment method is enhanced by the use of at least one classifier based on a plurality of focus classification features. In one application, a primary advantage of assessing focus from a single image is that an overall workpiece inspection time may be reduced by avoiding running an autofocus routine if an image is already in focus. In various embodiments, the focus assessment method may include an ensemble of classifiers. The ensemble of classifiers can be trained on different training data (sub)sets or different parameter (sub)sets, and their classification outcomes combined by a voting operation or the like, in order to enhance the overall accuracy and robustness of the focus assessment method.

A method and an apparatus for identifying motor vehicles for monitoring traffic. The identification is carried out by image-evaluation and includes determining the size ratios of a license-plate contour in a perspectively distorted image on the basis of stored standardized license-plate formats, determining the size of the perspective distortion of the license-plate contour on the basis of the associated standardized license-plate format, establishing a calculation rule for the perspective rectification on the basis of the ascertained distortion of the license-plate contour with respect to the associated license-plate format, rectifying the extracted license-plate-containing motor-vehicle view, and comparing the rectified image with reference images of front views of motor vehicles stored in a database in order to assign the image with greatest correspondence to a group of classified motor vehicles.

An adhesive robot, comprising a device for applying adhesive to a workpiece. The adhesive robot has a nozzle head (18), which has an application nozzle (24) and can be supplied with a pressurized viscous adhesive, the nozzle head (18) and the workpiece (14) being displaceable in relation to one another. The adhesive which is issued from the application nozzle (24) in a spray jet (28) is applied to a workpiece (14) along a predefined line of application (36) in the form of a strip of adhesive (40). To facilitate the adjustment and re-calibration process, the system comprises at least one camera unit (42), which is located on the nozzle head (18) and whose leans is directed towards the spray jet (28) or the adhesive strip (40). The output of said camera unit is connected to an image evaluation unit (45). The image data (40) recorded by the camera unit (42) is buffered and compared with predetermined image values (40). The decisive control parameters for the system can be calibrated and tracked either automatically or by remote control, on the basis of deviations in the image data that have been determined along the line of application (36).