Abstract: A computer implemented method and system determines a center point of a circular object in an image. A circular object identification system identifies prospective center points of the circular object for each of multiple pixel points at a predetermined distance along a gradient direction determined for each of the pixel points, constructs an axis between the corresponding prospective center points and a corresponding pixel point, and locates prospective circumference points at predetermined angles from the constructed axis.

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 determines a center point of a circular object in an image. A circular object identification system identifies prospective center points of the circular object for each of multiple pixel points at a predetermined distance along a gradient direction determined for each of the pixel points, constructs an axis between the corresponding prospective center points and a corresponding pixel point, and locates prospective circumference points at predetermined angles from the constructed axis.

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 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.