Tandent Vision Science, Inc.

Kshitiz Garg

Andrew Neil Stein

Casey Arthur Smith

Neil Alldrin

Bruce Allen Maxwell

Youngrock R Yoon

Kristin Jean Dana

Besma Roui Abidi

Albert Yen Cheng Chen

In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image file depicting an image, in a computer memory, identifying shadow edges in the image, computing gradient information for the image and modifying the gradient information relative to the shadow edges for improved performance of computer functionality in an image processing operation.

Pipeline for generating an intrinsic image

A soft, weighted constraint imposed upon image locations can be used to provide a more accurate segregation of an image into intrinsic material reflectance and illumination components. The constraint is arranged to constrain all color band variations between the image locations into one integral constraining relationship.

Constraint relationship for use in an image segregation

A method and system comprising image processing techniques is provided that utilize spatio-spectral information relevant to an image, derived from multiple sets of selectively varied representations of the image to accurately and correctly identify illumination and material aspects of the image. In an exemplary embodiment of the present invention, a scale-spaced pyramid arrangement is provided to preserve the purity of color from scale to scale, to insure accuracy in the identification of illumination and material aspects of the image.

Color pure scale-spaced pyramid arrangement for use in an image segregation

A soft, weighted constraint imposed upon image locations temporally spaced in frames of a video, can be used to provide a more accurate segregation of an image into intrinsic material reflectance and illumination components. The constraint is arranged to constrain all color band variations between the image locations into one integral constraining relationship.

Temporal constraint relationship for use in an image segregation for frames of a video

In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image file depicting an image, in a computer memory, providing a multi-class classifier trained to identify edges in an image relative to computer actions to be taken in respect to the respective edges, determined as a function of illumination effects in the image and utilizing the multi-class classifier to classify edges in the image, for identification of computer actions to be taken in respect to the edges in the image.

Classifier for use in generating a diffuse image

In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image file depicting an image, in a computer memory, assembling a feature vector for the image file, the feature vector containing information regarding a likelihood that a selected region of the image file is specular, providing a classifier derived from a computer learning technique, computing a classification score for the selected region of the image file, as a function of the feature vector and the classifier and classifying the region as being specular, as a function of the classification score.

System and method for detection of specularity in an image

In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image file depicting an image, in a computer memory, processing the image to generate intrinsic images including a material image and an illumination image, and detecting and removing specularity as a function of the intrinsic images.

System and method for removing specularity from an image

In a first exemplary embodiment of the present invention, an automated, computerized method is provided for processing an image. According to a feature of the present invention, the method comprises the steps of providing an image file depicting an image, in a computer memory, assembling a feature vector for the image file, the feature vector containing information regarding a likelihood that a selected pair of regions of the image file are of a same intrinsic characteristic, for example, a same texture, providing a classifier derived from a computer learning technique, computing a classification score for the selected pair of regions of the image file, as a function of the feature vector and the classifier and classifying the regions as being of the same intrinsic characteristic, as a function of the classification score.

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Pittsburgh, PA, United States of America

Kshitiz Garg