Abstract: A system for performing a scene representation procedure includes an image manager that processes source images from a given scene to define subscenes in the source images. The image manager creates an image understanding graph for each of the source images, and also creates a scene representation graph for each of the source images based upon the corresponding subscenes and certain image characteristics. The image manager further generates an integrated scene representation to represent all of the source images with a single representation. A processor of an electronic device controls the image manager to perform the scene representation procedure.

Abstract: Certain aspects of an apparatus and method for orienting tissue samples for comparison may include incrementally rotating orientation of a first image by a predetermined rotation angle while maintaining orientation of a second image at a fixed angle, checking alignment of the orientation of the first image with the orientation of the second image at each predetermined rotation angle by matching a plurality of points in the first image and the second image, determining whether a predetermined rotation angle is a correct rotation angle for alignment based on a count of the plurality of points being greater than a threshold value and rotating to the next predetermined rotation angle when the count of the plurality of points is less than or equal to a threshold value.

Abstract: A method for detecting presence of a hand gesture in video frames includes receiving video frames having an original resolution, downscaling the received video frames into video frames having a lower resolution, and detecting a motion corresponding to the predefined hand gesture in the downscaled video frames based on temporal motion information in the downscaled video frames. The method also includes detecting a hand shape corresponding to the predefined hand gesture in a candidate search window within one of the downscaled video frames using a binary classifier. The candidate search window corresponds to a motion region containing the detected motion. The method further includes determining whether the received video frames contain the predefined hand gesture based on the hand shape detection.

Abstract: A method for synchronizing navigation in pathology stain images includes (a) downscaling the pathology stain images, (b) estimating rotation of the downscaled images, (c) aligning the downscaled images to generate aligned coordinates, and (d) transforming the aligned coordinates to original image coordinates in the pathology stain images to thereby generate alignment data. Also provided is a system for synchronized navigation in pathology stain images having original resolutions comprising a downscaler, a rotation estimator, an alignment module, and a coordinate transformer. The system may also include an image display system to display corresponding areas of the pathology stain images.

Abstract: Systems and methods are disclosed for estimating a vanishing point within an image, including: programming executable on a processor for computing line segment estimation of one or more lines in an image, wherein one or more of the lines is made up of multiple line segments as a single least-mean-square-error (LMSE) fitted line. Additionally, the one or more lines having multiple line segments are represented as a single least-mean-square-error (LMSE) fitted line, and the one or more lines are intersected to locate a vanishing point in a density space.

Abstract: Certain aspects of an apparatus and method for method and apparatus for tissue region identification may include segmenting the image into a plurality of regions, filtering out regions in the plurality of regions which are curvilinear, and isolating a target area where the tissue sample is identified as the plurality of regions not filtered.

Abstract: Certain aspects of an apparatus and method for orienting tissue samples for comparison may include incrementally rotating orientation of a first image by a predetermined rotation angle while maintaining orientation of a second image at a fixed angle, checking alignment of the orientation of the first image with the orientation of the second image at each predetermined rotation angle by matching a plurality of points in the first image and the second image, determining whether a predetermined rotation angle is a correct rotation angle for alignment based on a count of the plurality of points being greater than a threshold value and rotating to the next predetermined rotation angle when the count of the plurality of points is less than or equal to a threshold value.

Abstract: A gesture recognition system and method that inputs videos of a moving hand and outputs the recognized gesture states for the input sequence. In each image, the hand area is segmented from the background and used to estimate parameters of all five fingers. The system further classifies the hand image as one of the postures in the pre-defined database and applies a geometric classification algorithm to recognize the gesture. The system combines a skin color model with motion information to achieve real-time hand segmentation performance, and considers each dynamic gesture as a multi-dimensional volume and uses a geometric algorithm to classify each volume.

Abstract: A method for automatically aligning images includes (a) determining initial correspondent point features between a first image and a second image, (b) creating a triangular meshes for the images from the initial correspondent point features within the images, and (c) refining point correspondence between the first and second images based on affine transformation estimation using the triangular meshes. The method may also include (d) creating refined triangular meshes for the images from the point correspondence refined in (c), and (e) determining coordinate alignment within the areas of pairs of correspondent triangles in the refined triangular meshes through interpolation of affine transformation on the pairs of correspondent triangles.

Abstract: A method for synchronizing navigation in pathology stain images includes (a) downscaling the pathology stain images, (b) estimating rotation of the downscaled images, (c) aligning the downscaled images to generate aligned coordinates, and (d) transforming the aligned coordinates to original image coordinates in the pathology stain images to thereby generate alignment data. Also provided is a system for synchronized navigation in pathology stain images having original resolutions comprising a downscaler, a rotation estimator, an alignment module, and a coordinate transformer. The system may also include an image display system to display corresponding areas of the pathology stain images.

Abstract: A method for automatically aligning images includes (a) determining initial correspondent point features between a first image and a second image, (b) creating a triangular meshes for the images from the initial correspondent point features within the images, and (c) refining point correspondence between the first and second images based on affine transformation estimation using the triangular meshes. The method may also include (d) creating refined triangular meshes for the images from the point correspondence refined in (c), and (e) determining coordinate alignment within the areas of pairs of correspondent triangles in the refined triangular meshes through interpolation of affine transformation on the pairs of correspondent triangles.

Abstract: A system for performing an image categorization procedure includes an image manager with a keypoint generator, a support region filter, an orientation filter, and a matching module. The keypoint generator computes initial descriptors for keypoints in a test image. The support region filter and the orientation filter perform respective filtering procedures upon the initial descriptors to produce filtered descriptors. The matching module compares the filtered descriptors to one or more database image sets for categorizing said test image. A processor of an electronic device typically controls the image manager to effectively perform the image categorization procedure.

Abstract: A system for performing a scene representation procedure includes an image manager that processes source images from a given scene to define subscenes in the source images. The image manager creates an image understanding graph for each of the source images, and also creates a scene representation graph for each of the source images based upon the corresponding subscenes and certain image characteristics. The image manager further generates an integrated scene representation to represent all of the source images with a single representation. A processor of an electronic device controls the image manager to perform the scene representation procedure.

Abstract: A system and method for effectively performing an image identification procedure includes an image matching manager that derives source characteristics for a source image and target characteristics for target images. The image matching manager compares the source characteristics and the target characteristics to determine whether the source image matches any of the target images. The source characteristics and the target characteristics may include color-space characteristics and curve-space characteristics from the respective images. A processor of an electronic device typically controls the image matching manager to effectively perform the image identification procedure.

Abstract: A method of and an apparatus for automatically estimating the tilting angle in tilted images enables level correction of the images. A preferred orientation of objects in an image and the deviation of the current orientation from the preferred orientation is determined by tilt image analysis without object recognition. Tilt image analysis includes several steps such as gradient feature computation, line segment tracking, line segment estimation and orientation deviation estimation. Once the tilt angle is determined, the image can be corrected so that an object or scene is not tilted or is tilted by only the appropriate amount.

Abstract: A system and method for effectively performing a scene rectification procedure comprises an image manager that includes a segmentation module, a label module, and a rectification module. The segmentation module initially performs a segmentation procedure upon an image to produce corresponding sub-scenes. The label module then categorizes the sub-scenes by assigning initial labels without utilizing context information from other sub-scenes in the image. The rectification module performs a semantic grouping procedure upon the sub-scenes to produce semantic group nodes corresponding to pairs of the sub-scenes that have a predefined semantic relationship. The rectification module converts a sub-scene graph of the sub-scenes into a semantic graph that includes the semantic group nodes. The rectification module then performs a rectification procedure to convert the initial labels of the sub-scenes into rectified labels.

Abstract: A system and method for effectively performing an integrated segmentation procedure comprises an image segmenter that includes a texture modeler, a contrast modeler, and a model integrator. The texture modeler creates a texture model based upon an original image. Similarly, the contrast modeler creates a contrast model based upon the original image. The model integrator then performs a model integration procedure to create a final segmented image by integrating the texture model and the contrast model according to a calculated texture model metric. A processor of an electronic device typically controls the image segmenter to perform the integrated segmentation procedure.

Abstract: A system and method for effectively performing an image identification procedure includes an image matching manager that derives source characteristics for a source image and target characteristics for target images. The image matching manager compares the source characteristics and the target characteristics to determine whether the source image matches any of the target images. The source characteristics and the target characteristics may include color-space characteristics and curve-space characteristics from the respective images. A processor of an electronic device typically controls the image matching manager to effectively perform the image identification procedure.

Abstract: A system and method for effectively performing a scene rectification procedure comprises an image manager that includes a segmentation module, a label module, and a rectification module. The segmentation module initially performs a segmentation procedure upon an image to produce corresponding sub-scenes. The label module then categorizes the sub-scenes by assigning initial labels without utilizing context information from other sub-scenes in the image. The rectification module performs a semantic grouping procedure upon the sub-scenes to produce semantic group nodes corresponding to pairs of the sub-scenes that have a predefined semantic relationship. The rectification module converts a sub-scene graph of the sub-scenes into a semantic graph that includes the semantic group nodes. The rectification module then performs a rectification procedure to convert the initial labels of the sub-scenes into rectified labels.

Abstract: System and methods for estimating a vanishing point within an image, including comprising: programming executable on a processor for computing line segment estimation of one or more lines in said image, wherein one or more of the lines comprise multiple line segments as a single least-mean-square-error (LMSE) fitted lines. Additionally the one or more lines having multiple line segments are represented as a single least-mean-square-error (LMSE) fitted line, and the one or more lines are intersected to locate a vanishing point in a density space.