Abstract: Automatic measurement of morphometric and motion parameters of a coronary target includes extracting reference frames from input data of a coronary target at different phases of a cardiac cycle, extracting a three-dimensional centerline model for each phase of the cardiac cycle based on the references frames and projection matrices of the coronary target, tracking a motion of the coronary target through the phases based on the three-dimensional centerline models, and determining a measurement of morphologic and motion parameters of the coronary target based on the motion.

Abstract: A method wherein images of different types of objects within a class are partitioned into region stacks. For each one of the stacks, the method: (a) applies a template to extract fragments having a predetermined size and one of a plurality of different spatial orientations, to generate extracted templates; (b) determines, from the extracted templates, a most frequent one thereof having only a first number of fragments with a common spatial orientations; (c) records the number of images having the determined most frequent extracted template; (d) repeats (b) and (c) with successively increasing number of fragments until the number of recoded images falls below a threshold; and (e) selects as a master extracted template the one of the most frequent templates having the largest recorded number of fragments. The master extracted templates for the stacks are combined into a map that is then compared with background images to remove extracted templates matching segment in the background.

Abstract: A method for modeling a vehicle, includes: receiving an image that includes a vehicle; and constructing a three-dimensional (3D) model of the vehicle, wherein the 3D model is constructed by: (a) taking a predetermined set of base shapes that are extracted from a subset of vehicles; (b) multiplying each of the base shapes by a parameter; (c) adding the resultant of each multiplication to form a vector that represents the vehicle's shape; (d) fitting the vector to the vehicle in the image; and (e) repeating steps (a)-(d) by modifying the parameters until a difference between a fit vector and the vehicle in the image is minimized.

Abstract: A method for compensating respiratory motion in coronary fluoroscopic images includes finding a set of transformation parameters of a parametric motion model that maximize an objective function that is a weighted normalized cross correlation function of a reference image acquired at a first time that is warped by the parametric motion model and a first incoming image acquired at a second time subsequent to the first time. The weights are calculated as a ratio of a covariance of the gradients of the reference image and the gradients of the first incoming image with respect to a root of a product of a variance of the gradients of the reference image and the variance of the gradients of the first incoming image. The parametric motion model transforms the reference image to match the first incoming image.

Abstract: Automatic measurement of morphometric and motion parameters of a coronary target includes extracting reference frames from input data of a coronary target at different phases of a cardiac cycle, extracting a three-dimensional centerline model for each phase of the cardiac cycle based on the references frames and projection matrices of the coronary target, tracking a motion of the coronary target through the phases based on the three-dimensional centerline models, and determining a measurement of morphologic and motion parameters of the coronary target based on the motion.

Abstract: A method for automatically detecting and tracking objects in a scene. The method acquires video frames from a video camera; extracts discriminative features from the video frames; detects changes in the extracted features using background subtraction to produce a change map; uses the change map to use a hypothesis to estimate of an approximate number of people along with uncertainty in user specified locations; and using the estimate, track people and update the hypotheses for a refinement of the estimation of people count and location.

Abstract: A method of tracking a pose of a moving camera includes receiving a first image from a camera, receiving a sequence of digitized images from said camera, recording, for each of said sequence of digitized images, the pose and 2D correspondences of landmarks, reconstructing a location and appearance of a 2-dimensional texture patch from 2D correspondences of the landmarks by triangulation and optimization, computing back-projection errors by comparing said reconstructed texture patch with said first received image; and reconstructing said location and appearance of said 2-dimensional texture patch from the 2D correspondences of the landmarks of said sequence of digitized images by triangulation and optimization after eliminating those landmarks with large back-projection errors.

Abstract: A method for modeling a vehicle, includes: receiving an image that includes a vehicle; and constructing a three-dimensional (3D) model of the vehicle, wherein the 3D model is constructed by: (a) taking a predetermined set of base shapes that are extracted from a subset of vehicles; (b) multiplying each of the base shapes by a parameter; (c) adding the resultant of each multiplication to form a vector that represents the vehicle's shape; (d) fitting the vector to the vehicle in the image; and (e) repeating steps (a)-(d) by modifying the parameters until a difference between a fit vector and the vehicle in the image is minimized.

Abstract: A method wherein images of different types of objects within a class are partitioned into region stacks. For each one of the stacks, the method: (a) applies a template to extract fragments having a predetermined size and one of a plurality of different spatial orientations, to generate extracted templates; (b) determines, from the extracted templates, a most frequent one thereof having only a first number of fragments with a common spatial orientations; (c) records the number of images having the determined most frequent extracted template; (d) repeats (b) and (c) with successively increasing number of fragments until the number of recoded images falls below a threshold; and (e) selects as a master extracted template the one of the most frequent templates having the largest recorded number of fragments. The master extracted templates for the stacks are combined into a map that is then compared with background images to remove extracted templates matching segment in the background.

Abstract: A method of generating a resulting image includes generating a superimposed image by aligning and superimposing one or more transposed images with a reference image by using offsets of the one or more transposed images from the reference image, generating an intermediate image from the superimposed image, generating a new superimposed image by aligning and superimposing the intermediate image, the one or more transposed images and the reference image by using offsets of the one or more transposed images and the reference image from the intermediate image, and generating a resulting image from the new superimposed image.

Abstract: A method of tracking a pose of a moving camera includes receiving a first image from a camera, receiving a sequence of digitized images from said camera, recording, for each of said sequence of digitized images, the pose and 2D correspondences of landmarks, reconstructing a location and appearance of a 2-dimensional texture patch from 2D correspondences of the landmarks by triangulation and optimization, computing back-projection errors by comparing said reconstructed texture patch with said first received image; and reconstructing said location and appearance of said 2-dimensional texture patch from the 2D correspondences of the landmarks of said sequence of digitized images by triangulation and optimization after eliminating those landmarks with large back-projection errors.

Abstract: A system and method for tracking parcels on a planar surface is provided. The method comprising: acquiring an image of the parcel located on the planar surface; determining edges of the parcel; projecting the edges onto the planar surface; determining which edges belong to each side of the parcel; calculating a cost function associated with the edges belonging to each side of the parcel; searching the edges belonging to each side of the parcel to find edges having a lowest cost; and constructing a matching configuration of the parcel using the edges having the lowest cost.