Abstract: A human subject is tracked within a scene of an observed depth image supplied to a general-purpose body-part tracker. The general-purpose body-part tracker is retrained for a specific scenario. The general-purpose body-part tracker was previously trained using supervised machine learning to identify one or more general-purpose parameters to be used by the general-purpose body-part tracker to track a human subject. During a retraining phase, scenario data is received that represents a human training-subject performing an action specific to a particular scenario. One or more special-purpose parameters are identified from the processed scenario data. The special-purpose parameters are selectively used to augment or replace one or more general-purpose parameters if the general-purpose body-part tracker is used to track a human subject performing the action specific to the particular scenario.

Abstract: A system and associated methodology recognizes an Arabic like alphanumeric character using fuzzy modeling. The method receives a handwritten Arabic like alphanumeric character, stores fuzzy models of a plurality of Arabic like alphanumeric characters, preprocesses the handwritten Arabic like alphanumeric character, extracts features from the preprocessed Arabic like alphanumeric character, computes a similarity value based on fuzzy comparison between points of the preprocessed Arabic like alphanumeric character and the stored fuzzy models, classifies the handwritten Arabic like alphanumeric character based at least in part on the similarity value and outputs a classified alphanumeric character.

Abstract: An analysis of a digitized image is provided. The digitized image is repeatedly convolved to form first convolved images, which first convolved images are convolved a second time to form second convolved images. Each first convolved image and the respective second convolved image representing a stage, and each stage represents a different scale or size of anomaly. As an example, the first convolution may utilize a Gaussian convolver, and the second convolution may utilize a Laplacian convolver, but other convolvers may be used. The second convolved image from a current stage and the first convolved image from a previous stage are used with a neighborhood median determined from the second convolved image from the current stage by a peak detector to detect peaks, or possible anomalies for that particular scale.

Abstract: The noise of a detection value acquired by an imaging system (30) can depend on the contributions of different components within a region of interest to be imaged, which has been traversed by radiation (4) causing the respective acquired detection value. This dependence is considered while iteratively reconstructing an image of the region of interest, wherein first component attenuation values, which correspond to elements of a first component within the region of interest, and second component attenuation values, which correspond to elements of a first component within the region of interest, are determined, wherein noise values are determined from the first component attenuation values and the second component attenuation values and wherein the noise values are used for updating the image. This consideration of the dependence of the noise of an acquired detection value on the different components improves the quality of the iteratively reconstructed image.

Abstract: An appearance inspection apparatus comprises an inspection part for detecting a defect of a pattern on the basis of an image of a surface of a substrate on which the pattern is formed, which is captured by an imaging part. The inspection part comprises an image transfer part for transferring image data which is obtained by imaging a region to be inspected on the substrate and stored in an image storing memory by the imaging part to a plurality of image processing memories and a plurality of GPUs for taking image data corresponding to respective regions to be processed out of transferred image data which are transferred to the image processing memories by the image transfer part and performing an inspection process for defect detection on the image data.

Abstract: A method for processing handwriting input includes determining a first boundary point and a second boundary point corresponding to each target track point, forming an enclosed area by connecting all first boundary points determined for all target track points, connecting all second boundary points determined for all the target track points, connecting the first boundary point corresponding to the first target track point with the second boundary point corresponding to the first target track point, and connecting the first boundary point corresponding to the last target track point with the second boundary points corresponding to the last target track point, and filling the enclosed area.

Abstract: System and method are provided for determining hair tail positions. An image containing hair which is received from an image acquisition device is processed to find a coarse hair tail position. The coarse hair tail position is refined through further processing. The refined hair tail position may be used for accurate positioning, for example, of hair transplantation tools in various hair transplantation applications.

Abstract: A system and method for analyzing video include segmenting video stored in computer readable storage media into keyframes. Near-duplicate keyframes are represented as a sequence of indices. The near-duplicate keyframes are rendered in a graphical representation to determine relationships between video content.

Abstract: For the purpose of 3D scanning the surface of an object by optical double triangulation using the phase-shifting method, more particularly for dental purposes, at least two 3D scans of the same object (1) are carried out at different triangulation angles (?1, ?2), the first angle of which is known and the second angle of which is known at least approximately. For each pixel (Bi) of the phase related image (?1(x,y)), a wave number (wz(xi,yi) is determined using the second phase related image, the integral portion of which is equal to the order (n) of the uniqueness range (E1) in which the respective pixel (Bi) is located. The wave number (wz(x,y)) is optimized, at least for a random sample of m pixels (Bi), by minimizing a non-integral portion of the wave number (wz (xi,yi)?[wz(xi,yi)]).

Abstract: Photographs of an object may be oriented with respect to both the geographic location and orientation of the object by registering a 3D model derived from a plurality of photographs of the objects with a 2D image of the object having a known location and orientation. For example, a 3D point cloud of an object created from photographs of the object using a Photosynth™ tool may be aligned with a satellite photograph of the object, where the satellite photograph has location and orientation information. A tool providing scaling and rotation of the 3D model with respect to the 2D image may be used or an automatic alignment may be performed using a function based on object edges filtered at particular angles. Once aligned, data may be recorded that registers camera locations for the plurality of photographs with geographic coordinates of the object, either absolute latitude/longitude or relative to the object.

Abstract: An image recognition part of an image recognition apparatus recognizes an object based on a target area in an outside-vehicle image obtained by a camera installed in a vehicle. A position identifying part identifies an optical axis position of the camera relative to the vehicle based on the outside-vehicle image, and an area changing part changes a position of the target area in the outside-vehicle image according to the optical axis position of the camera. Therefore, it is possible to recognize an object properly based on the target area in the outside-vehicle image even though the optical axis position of the camera is displaced.

Abstract: One or more techniques and/or systems for detecting edges in images of objects subjected to imaging using imaging apparatus are disclosed, such that the effect of image noise on the edge detection can be mitigated. Ratios of intensity values (e.g., signal values) for a subject region (e.g., a pixel) and respective adjacent regions are determined. An adaptive threshold value is determined for respective adjacent region pairs. The ratio value is compared to the adaptive threshold value for respective adjacent region pairs, to determine whether an edge is present between the respective adjacent region pairs.

Abstract: The invention relates to an apparatus and method for visually representing measuring values. The present invention starts out from the idea of veiling the visual representation of authenticity data or other measuring values by visually representing not the measuring values themselves, but camouflage data, which are formed by measuring values changed with the help of a mathematical algorithm.

Abstract: A method for three-dimensional esophageal reconstruction includes acquiring a first X-ray image from a first angle with respect to a subject using a first X-ray imager. At least a second X-ray image is acquired from a second angle, different than the first angle, with respect to the subject using a second X-ray imager. Additional X-ray images may be acquired from additional angle. A three-dimensional model of the esophagus is generated from the at least two X-ray images acquired at different angles. A set of fluoroscopic X-ray images is acquired using either the first X-ray imager or the second X-ray imager. The three-dimensional model of the esophagus is registered to the acquired set of fluoroscopic X-ray images. The three-dimensional model of the esophagus is displayed overlaying the set of fluoroscopic X-ray images.

Abstract: This invention makes it possible to obtain an enlarged image while suppressing noise and maintaining the sharpness of an original image only by setting a simple enlargement ratio without no special knowledge. Original image data (Ia) is enlarged in accordance with a set enlargement ratio (E) to generate an enlarged image (IA). The enlarged image (IA) is smoothed by using a smoothing filter with a size depending on the enlargement ratio (E) to generate smoothed image data (IB). Difference image data (IC) is generated by calculating the difference between the enlarged image data (IA) and the smoothed image data (IB). The generated difference image data is multiplied by an emphasis coefficient. The product is added to the enlarged image data, thereby obtaining image data (IS) that has undergone enlargement/unsharp masking.

Abstract: A bit rate control circuit for image compression includes a compression unit, a R-value calculation unit, a linear quantization factor (LQF) calculation unit. The compression unit is used to performs a first quantization process on an image based on a default LQF (LQFini) to obtain an initial bits per pixel (bbpini) with an initial number of zero coefficients (Rini). The R-value calculation unit calculates out a target R value (Rtarget) based on the initial bits per pixel (bbpini), the initial number zero coefficients (Rini), and a target bpp (bbptarget). The LQF calculation unit calculates a target LQF (LQFtarget) based on the target R value Rtarget. The LQFtarget can be used to perform a second compression on the image to obtain a compressed image corresponding to the target bpp (bpptarget).

Abstract: There is described an analysis method for at least one image data record of an examination object, wherein each image data record features a multiplicity of image data elements. A position in a multidimensional space is assigned to each image data element. Each image data element features an image data value. The image data values of positionally corresponding image data elements of the image data records are specified by means of at least essentially positionally identical regions of the examination object. A computer automatically divides the image data records into empty regions and signal regions, applying an overall assignment rule which is based on the image data values of the image data elements of a plurality of image data records, such that each image data element of each image data record is assigned to either its empty region or its signal region.