Abstract: An object detector that includes a number of weak classifiers can be trained using a subset (a “working set”) of training data instead of all of the training data. The working set can be updated so that, for example, it remains representative of the training data. A decision to update the working set may be made based on the false positive sample rate—if that rate falls below a threshold value, an update of the working set can be triggered.

Abstract: An efficient, effective and at times superior object detection and/or recognition (ODR) function may be built from a set of Bayesian stumps. Bayesian stumps may be constructed for each feature and object class, and the ODR function may be constructed from the subset of Bayesian stumps that minimize Bayesian error for a particular object class. That is, Bayesian error may be utilized as a feature selection measure for the ODR function. Furthermore, Bayesian stumps may be efficiently implemented as lookup tables with entries corresponding to unequal intervals of feature histograms. Interval widths and entry values may be determined so as to minimize Bayesian error, yielding Bayesian stumps that are optimal in this respect.

Abstract: A method of isolating a pluripotent cell from human umbilical cord is described herein. The method involves collecting a sample of umbilical cord from fetal tissue obtained at less than 20 weeks of gestation, for example a first trimester umbilical cord. The sample is treated to obtain isolated umbilical cord cells, after which the isolated umbilical cord cells are incubated. Stem cells obtained in this way can be differentiated for use in therapeutic applications.

Abstract: Systems and methods are described for a face annotation framework with partial clustering and interactive labeling. In one implementation, an exemplary system automatically groups some images of a collection of images into clusters, each cluster mainly including images that contain a person's face associated with that cluster. After an initial user-labeling of each cluster with the person's name or other label, in which the user may also delete/label images that do not belong in the cluster, the system iteratively proposes subsequent clusters for the user to label, proposing clusters of images that when labeled, produce a maximum information gain at each iteration and minimize the total number of user interactions for labeling the entire collection of images.

Abstract: An interactive photo annotation method uses clustering based on facial similarities to improve annotation experience. The method uses a face recognition algorithm to extract facial features of a photo album and cluster the photos into multiple face groups based on facial similarity. The method annotates a face group collectively using annotations, such as name identifiers, in one operation. The method further allows merging and splitting of face groups. Special graphical user interfaces, such as displays in a group view area and a thumbnail area and drag-and-drop features, are used to further improve the annotation experience.

Abstract: The present invention includes compositions and methods related to the structure and function of the cellular polyadenylation and specificity factor 30 (CPSF30) binding site on the surface of the influenza A non-structural protein 1 (NS1). Specifically, critical biochemical reagents, conditions for crystallization and NMR analysis, assays, and general processes are described for (i) discovering, designing, and optimizing small molecule inhibitors of influenza A (avian flu) viruses and (ii) creating attenuated influenza virus strains suitable for avian and human flu vaccine development.

Abstract: Methods and systems are provided for selecting features that will be used to recognize faces. Three-dimensional models are used to synthesize a database of virtual face images. The virtual face images cover wide appearance variations, different poses, different lighting conditions and expression changes. A joint boosting algorithm is used to identify discriminative features by selecting features from the plurality of virtual images such that the identified discriminative features are independent of the other images included in the database.

Abstract: Systems and methods are described for robust online face tracking. In one implementation, a system derives multiple resolutions of each video frame of a video sequence portraying movement of a visual object. The system tracks movement of the visual object in a low resolution as input for tracking the visual object in a higher resolution. The system can greatly reduce jitter while maintaining an ability to reliably track fast-moving visual objects.

Abstract: A method and system for detecting faces at different views within images that allocates the computational effort based on a prior probability associated with a view is provided. A face detection system determines whether an image contains a face using detectors that are adapted to detect faces at various views and a filter that filters out windows of the image that are provided to a detector based on a prior probability associated with the view of the detector. Each view has an associated prior probability that a face from a collection of real-life home photographs will be at that view. The face detection system allocates increasing computational effort to a detector as the prior probability of its view increases.

Abstract: Face detection techniques are provided that use a multiple-stage face detection algorithm. An exemplary three-stage algorithm includes a first stage that applies linear-filtering to enhance detection performance by removing many non-face-like portions within an image, a second stage that uses a boosting chain that is adopted to combine boosting classifiers within a hierarchy “chain” structure, and a third stage that performs post-filtering using image pre-processing, SVM-filtering and color-filtering to refine the final face detection prediction. In certain further implementations, the face detection techniques include a two-level hierarchy in-plane pose estimator to provide a rapid multi-view face detector that further improves the accuracy and robustness of face detection.