Abstract: Various embodiments are directed to a Pose Correction Engine (“Engine”). The Engine generates a reference image of the object of interest. The reference image portrays the object of interest oriented according to a first pose. The Engine receives a source image of an instance of the object. The source image portrays the instance of the object oriented according to a variation of the first pose. The Engine determines a difference between the first pose of the reference image and the variation of the first pose of the source image. The Engine identifies, based on the determined difference, one or portions of a three-dimensional (3D) map of a shape of the object obscured by the variation of the first pose portrayed in the source image. The Engine generates a pose corrected image of the instance of the object that portrays at least a portion of the source image and at least the identified portion of the 3D map of the shape of the object.

Abstract: Various embodiments are directed to a Pose Correction Engine (“Engine”). The Engine generates a reference image of the object of interest. The reference image portrays the object of interest oriented according to a first pose. The Engine receives a source image of an instance of the object. The source image portrays the instance of the object oriented according to a variation of the first pose. The Engine determines a difference between the first pose of the reference image and the variation of the first pose of the source image. The Engine identifies, based on the determined difference, one or portions of a three-dimensional (3D) map of a shape of the object obscured by the variation of the first pose portrayed in the source image. The Engine generates a pose corrected image of the instance of the object that portrays at least a portion of the source image and at least the identified portion of the 3D map of the shape of the object.

Abstract: A computer implemented method and system for capturing events of interest by performing a spatio-temporal analysis of a video are provided. A continuous video stream containing a series of image frames is acquired over time. Each of the image frames is represented by horizontal spatial coordinates and vertical spatial coordinates of a two dimensional plane. A temporal dimension is assigned across the image frames of the video stream. A spatio-temporal analysis image is constructed based on a user-defined line of analysis on each of one or more of the image frames. The spatio-temporal analysis image is constructed by concatenating a series of temporally-successive linear pixel arrays along the temporal dimension. Each of the linear pixel arrays comprises an array of pixels along the line of analysis defined on each of one or more of the image frames. The constructed spatio-temporal analysis image is segmented for capturing the events of interest.

Abstract: A computer implemented method and system for detecting interest sections in a still image are provided. One or more sub images of the still image is subjected to segmentation. A gray scale version of interest sub images and/or a binary image version of the interest sub images are matched with a predefined template for filtering the interest sub images. Multiple prospective image sections comprising one or more of prospective interest sections and prospective near interest sections are determined by performing discriminative feature analyses of the filtered interest sub images using a gabor feature filter. The discriminative feature analyses are processed by a boosted cascade of classifiers. The boosted cascade of classifiers detects the interest sections in the still image from the prospective interest sections and the prospective near interest sections. The detected interest sections are subjected to a support vector machine classifier for further detecting interest sections.

Abstract: A computer implemented method and system is provided for aligning multiple overlapping images in real time using translation invariant feature matching. A user captures overlapping images comprising a first image and a second image using one or more image capture devices. An image aligning application determines one or more local maxima pixel points and local minima pixel points in the first image and the second image based on predetermined statistical criteria. The image aligning application performs iterative intra image correlation in the first image for selecting a predetermined number of feature points. The image aligning application performs iterative inter image correlation for the selected feature points, for determining a predetermined number of best correlated feature point pairs, and selects a matching feature point pair from the best correlated feature point pairs. The image aligning application aligns the first image and the second image using the selected matching feature point pair.

Abstract: A computer implemented method and system for capturing events of interest by performing a spatio-temporal analysis of a video are provided. A continuous video stream containing a series of image frames is acquired over time. Each of the image frames is represented by horizontal spatial coordinates and vertical spatial coordinates of a two dimensional plane. A temporal dimension is assigned across the image frames of the video stream. A spatio-temporal analysis image is constructed based on a user-defined line of analysis on each of one or more of the image frames. The spatio-temporal analysis image is constructed by concatenating a series of temporally-successive linear pixel arrays along the temporal dimension. Each of the linear pixel arrays comprises an array of pixels along the line of analysis defined on each of one or more of the image frames. The constructed spatio-temporal analysis image is segmented for capturing the events of interest.

Abstract: A computer implemented method and system for detecting interest sections in a still image are provided. One or more sub images of the still image is subjected to segmentation. A gray scale version of interest sub images and/or a binary image version of the interest sub images are matched with a predefined template for filtering the interest sub images. Multiple prospective image sections comprising one or more of prospective interest sections and prospective near interest sections are determined by performing discriminative feature analyses of the filtered interest sub images using a gabor feature filter. The discriminative feature analyses are processed by a boosted cascade of classifiers. The boosted cascade of classifiers detects the interest sections in the still image from the prospective interest sections and the prospective near interest sections. The detected interest sections are subjected to a support vector machine classifier for further detecting interest sections.

Abstract: A computer implemented method and system is provided for aligning multiple overlapping images in real time using translation invariant feature matching. A user captures overlapping images comprising a first image and a second image using one or more image capture devices. An image aligning application determines one or more local maxima pixel points and local minima pixel points in the first image and the second image based on predetermined statistical criteria. The image aligning application performs iterative intra image correlation in the first image for selecting a predetermined number of feature points. The image aligning application performs iterative inter image correlation for the selected feature points, for determining a predetermined number of best correlated feature point pairs, and selects a matching feature point pair from the best correlated feature point pairs. The image aligning application aligns the first image and the second image using the selected matching feature point pair.