Abstract: A method for face model fitting comprising, receiving a first observed image, receiving a second observed image, and fitting an active appearance model of a third image to the second observed image and the first observed image with an algorithm that includes a first function of a mean-square-error between a warped image of the second observed image and a synthesis of the active appearance model and a second function of a mean-square-error between the warped image of the second observed image and an appearance data of the first observed image.

Abstract: The system and method disclosed herein provides an integrated and automated workflow, sensor, and reasoning system that automatically detects breaches in protocols, appropriately alarms and records these breaches, facilitates staff adoption of protocol adherence, and ultimately enables the study of protocols for care comparative effectiveness. The system provides real-time alerts to medical personnel in the actual processes of care, thereby reducing the number of negative patient events and ultimately improving staff behavior with respect to protocol adherence.

Abstract: There is provided a discriminative framework for image alignment. Image alignment is generally the process of moving and deforming a template to minimize the distance between the template and an image. There are essentially three elements to image alignment, namely template representation, distance metric, and optimization method. For template representation, given a face dataset with ground truth landmarks, a boosting-based classifier is trained that is able to learn the decision boundary between two classes—the warped images from ground truth landmarks (e.g., positive class) and those from perturbed landmarks (e.g., negative class). A set of trained weak classifiers based on Haar-like rectangular features determines a boosted appearance model. A distance metric is a score from the strong classifier, and image alignment is the process of optimizing (e.g., maximizing) the classification score.

Abstract: A method and system for distributed tracking of multiple targets is disclosed. Multiple targets to be tracked by a plurality of trackers are detected in a frame. The motion state variable of each of the plurality of trackers is calculated in the E-step of a variational Expectation-Maximization algorithm. Further, the data association variable of each of the plurality of trackers is calculated in the M-step of the algorithm. Depending on the motion state variable and the data association variable, the multiple targets are tracked.

Abstract: A system and method for performing a facial image restoration is described. The system includes an active appearance model component for fitting an active appearance model to a facial image found in each of a plurality of video frames, a registration component for registering each pixel of each facial image with comparable pixels of each of the other facial images, and a restoration component for producing a restored facial image from the facial images. The method includes fitting an active appearance model to a facial image found in each of a plurality of video frames, registering each pixel of each said facial image with comparable pixels of each of the other facial images, and producing a restored facial image from the facial images.

Abstract: A method of producing an enhanced Active Appearance Model (AAM) by combining images of multiple resolutions is described herein. The method generally includes processing a plurality of images each having image landmarks and each image having an original resolution level. The images are down-sampled into multiple scales of reduced resolution levels. The AAM is trained for each image at each reduced resolution level, thereby creating a multi-resolution AAM. An enhancement technique is then used to refine the image landmarks for training the AAM at the original resolution level. The landmarks for training the AAM at each level of reduced resolution is obtained by scaling the landmarks used at the original resolution level by a ratio in accordance with the multiple scales.

Abstract: Embodiments of the invention include a system and a method for determining whether a person is carrying concealed contraband, such as an improvised explosives device or other weapon. The system includes a people tracking video subsystem, a people tracking decisioning subsystem, a concealed contraband detection aiming subsystem, and a concealed contraband detection decisioning subsystem.

Abstract: A technique for optimizing object recognition is disclosed. The technique includes receiving at least one image of an object and at least one reference image. The technique further includes identifying at least one performance metric corresponding to an object recognition task. The identified performance metric is optimized to generate the corresponding optimized performance metric by determining an optimal subspace based on a determined objective function corresponding to the object recognition task and a difference between the received image and the corresponding reference image. Subsequently, the technique includes comparing the received image with the reference image based on the optimized performance metric for performing the object recognition task.

Abstract: A system and method for estimating a set of landmarks for a large image ensemble employs only a small number of manually labeled images from the ensemble and avoids labor-intensive and error-prone object detection, tracking and alignment learning task limitations associated with manual image labeling techniques. A semi-supervised least squares congealing approach is employed to minimize an objective function defined on both labeled and unlabeled images. A shape model is learned on-line to constrain the landmark configuration. A partitioning strategy allows coarse-to-fine landmark estimation.

Abstract: A method for re-identifying an image is provided. The method comprises obtaining a plurality of images and generating a correspondence map between the plurality of images. The method further comprises defining a plurality of region signatures for one or more regions comprising the plurality of images and comparing the plurality of images based on the correspondence map and the plurality of region signatures to perform image re-identification.

Abstract: A system, method and apparatus for performing a facial approximation is described. The system includes an acquisition subsystem and a facial approximation algorithm. The method includes the steps of acquiring models of known skulls and a model of a questioned skull, comparing the models of the known skulls with the model of the questioned skull, and removing variation in the facial structure of the questioned skull due to skeletal variation between the known skulls and the questioned skull. The apparatus includes a bony structure software component, a bony structure warping software component, and a soft tissue software component.

Abstract: The present invention aims at providing a method for detecting a signal structure from a moving vehicle. The method for detecting signal structure includes capturing an image from a camera mounted on the moving vehicle. The method further includes restricting a search space by predefining candidate regions in the image, extracting a set of features of the image within each candidate region and detecting the signal structure accordingly.

Abstract: Embodiments of the invention include a security checkpoint system that has a camera configured for obtaining a first photographic image of an individual, a photographic image scanner configured for scanning a second photographic image, and a comparator mechanism for comparing the first photographic image with the second photographic image to ascertain whether the second photographic image is of the individual. Other embodiments include a method for automatedly developing security-related characteristics for an individual.

Abstract: A gaze estimation method and system, the method including capturing a video sequence of images with an image capturing system, designating at least one landmark in a head portion of the captured video sequence, fitting a virtual model of the head portion to the actual head portion in the captured video sequence, and determining the gaze estimation.

Abstract: A method for face model fitting comprising, receiving a first observed image, receiving a second observed image, and fitting an active appearance model of a third image to the second observed image and the first observed image with an algorithm that includes a first function of a mean-square-error between a warped image of the second observed image and a synthesis of the active appearance model and a second function of a mean-square-error between the warped image of the second observed image and an appearance data of the first observed image.

Abstract: A system for detecting and counting individuals in a stationary or moving crowd based on a digital or digitized image captured from a single camera. Initial information is assumed based on a foot-to-head plane homology, where a geometric construct is developed to best enclose image features with a high probability of being an individual within a crowd. These geometric constructs are then subjected to further probabilistic analysis to determine individuals. The vector track of each individual is determined to validate the determination of a group of features as individuals, thereby compensating for occlusion of an individual within any given frame image. A virtual gate is then employed to count the individuals moving past the virtual gate. Also, by weighting portions of the individual, events near the gate can be predicted.

Abstract: A method of image reconstruction comprising: obtaining a Helmholtz reciprocal pair of images of an object, the images comprising a first image and a corresponding reciprocal image; determining an imaging geometry associated with the obtaining; selecting a plurality of points in the first image and identifying corresponding candidate points in the corresponding reciprocal image; matching a selected point of the plurality of points and a candidate point of the corresponding candidate points. A method of image registration with an object comprising: obtaining a Helmholtz reciprocal pair of images of an object, the Helmholtz reciprocal pair of images comprising a first image and a corresponding reciprocal image; estimating a pose for the object; predicting an estimated image corresponding to the pose and one image of the reciprocal pair of images; comparing the estimated image with a corresponding actual image from the pair of images; and refining the estimating a pose based on the comparing.

Abstract: There is provided a discriminative framework for image alignment. Image alignment is generally the process of moving and deforming a template to minimize the distance between the template and an image. There are essentially three elements to image alignment, namely template representation, distance metric, and optimization method. For template representation, given a face dataset with ground truth landmarks, a boosting-based classifier is trained that is able to learn the decision boundary between two classes-the warped images from ground truth landmarks (e.g., positive class) and those from perturbed landmarks (e.g., negative class). A set of trained weak classifiers based on Haar-like rectangular features determines a boosted appearance model. A distance metric is a score from the strong classifier, and image alignment is the process of optimizing (e.g., maximizing) the classification score.

Abstract: A method and system for distributed tracking of multiple targets is disclosed. Multiple targets to be tracked by a plurality of trackers are detected in a frame. The motion state variable of each of the plurality of trackers is calculated in the E-step of a variational Expectation-Maximization algorithm. Further, the data association variable of each of the plurality of trackers is calculated in the M-step of the algorithm. Depending on the motion state variable and the data association variable, the multiple targets are tracked.

Abstract: A technique of adaptive advertising is provided. The technique includes obtaining at least one of demographic and behavioral profiles of a plurality of individuals in an environment and adjusting an advertising strategy in the environment of one or more products based upon the demographic and behavioral profiles of the plurality of individuals.