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 image alignment is disclosed. In one embodiment, the method includes acquiring a facial image of a person and using a discriminative face alignment model to fit a generic facial mesh to the facial image to facilitate locating of facial features. The discriminative face alignment model may include a generative shape model component and a discriminative appearance model component. Further, the discriminative appearance model component may have been trained to estimate a score function that minimizes the angle between a gradient direction and a vector pointing toward a ground-truth shape parameter. Additional methods, systems, and articles of manufacture are also disclosed.

Abstract: An imaging system is provided. The imaging system includes an X-ray radiation source. The imaging system also includes a source controller coupled to the X-ray radiation source and configured to modulate an exposure pattern from the X-ray radiation source to enable a coded exposure sequence. The imaging system further includes a digital X-ray detector configured to acquire image data that includes at least one coded motion blur.

Abstract: A generally lossless compression system suitable for compression of data in a real-time, remote monitoring application is disclosed. In one embodiment, the real-time monitoring application is subject to a fixed-delay transmission constraint. In one implementation, a specific set partitioning method (e.g., binary tree partitioning) is employed on blocks of data that are wavelet transformed in a reversible manner so that encoded blocks may be transmitted losslessly or truncated and transmitted with some loss.

Abstract: A method for image alignment is disclosed. In one embodiment, the method includes acquiring a facial image of a person and using a discriminative face alignment model to fit a generic facial mesh to the facial image to facilitate locating of facial features. The discriminative face alignment model may include a generative shape model component and a discriminative appearance model component. Further, the discriminative appearance model component may have been trained to estimate a score function that minimizes the angle between a gradient direction and a vector pointing toward a ground-truth shape parameter. Additional methods, systems, and articles of manufacture are also disclosed.

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 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 generally lossless compression system suitable for compression of data in a real-time, remote monitoring application is disclosed. In one embodiment, the real-time monitoring application is subject to a fixed-delay transmission constraint. In one implementation, a specific set partitioning method (e.g., binary tree partitioning) is employed on blocks of data that are wavelet transformed in a reversible manner so that encoded blocks may be transmitted losslessly or truncated and transmitted with some loss.

Abstract: A method for image alignment is disclosed. In one embodiment, the method includes acquiring a facial image of a person and using a discriminative face alignment model to fit a generic facial mesh to the facial image to facilitate locating of facial features. The discriminative face alignment model may include a generative shape model component and a discriminative appearance model component. Further, the discriminative appearance model component may have been trained to estimate a score function that minimizes the angle between a gradient direction and a vector pointing toward a ground-truth shape parameter. Additional methods, systems, and articles of manufacture are also disclosed.

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 is provided for accurately determining the registration for a moving vehicle over a number of frames so that the vehicle can be super-resolved. Instead of causing artifacts in a super-resolved image, the moving vehicle can be specifically registered and super-resolved individually. This method is very accurate, as it uses a mathematical model that captures motion with a minimal number of parameters and uses all available image information to solve for those parameters. Methods are provided that implement the vehicle registration algorithm and super-resolve moving vehicles using the resulting vehicle registration. One advantage of this system is that better images of moving vehicles can be created without requiring costly new aerial surveillance equipment.

Abstract: A system and method for contactless handprint capture is disclosed that includes an image capture device to capture whole handprint images of a subject hand at each of a plurality of different focal distances, with the image capture device including an imaging camera and an electro-optics arrangement having a plurality of light modulating elements and polarization sensitive optical elements having differing optical path lengths based on polarization states. A control system is coupled to the image capture device to cause the device to capture the handprint images at each of the different focal distances, with each handprint image having a depth-of-focus that overlaps with a depth-of-focus of handprint images at adjacent focal distances such that redundant handprint image data is captured. The control system registers each handprint image with positional data and creates a composite handprint image from the handprint images captured at the different focal distances.

Abstract: A method for image alignment is disclosed. In one embodiment, the method includes acquiring a facial image of a person and using a discriminative face alignment model to fit a generic facial mesh to the facial image to facilitate locating of facial features. The discriminative face alignment model may include a generative shape model component and a discriminative appearance model component. Further, the discriminative appearance model component may have been trained to estimate a score function that minimizes the angle between a gradient direction and a vector pointing toward a ground-truth shape parameter. Additional methods, systems, and articles of manufacture are also disclosed.

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: 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 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 technique is provided for performing diagnosis and/or analysis of a volumetric image generated via anatomy based reconstruction. The technique includes generating a three-dimensional image by reconstructing a plurality of residual projection images from which a contribution of one or more structures of interest has been removed. The technique also includes evaluating the three-dimensional image and/or the plurality of residual projection images to generate a diagnosis.

Abstract: An improved holographic data storage disc is provided. The holographic data storage disc includes multiple multimedia content, wherein at least one of the multimedia is locked via one or more cryptographic keys.

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: 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.