摘要:
Systems and methods for detecting doctored JPEG images are described. In one aspect, a JPEG image is evaluated to determine if the JPEG image comprises double quantization effects of double quantized Discrete Cosine Transform coefficients. In response to results of these evaluation operations, the systems and methods determine whether the JPEG image has been doctored and identify any doctored portion.
摘要:
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.
摘要:
Tensor linear Laplacian discrimination for feature extraction is disclosed. One embodiment comprises generating a contextual distance based sample weight and class weight, calculating a within-class scatter using the at least one sample weight and a between-class scatter for multiple classes of data samples in a sample set using the class weight, performing a mode-k matrix unfolding on scatters and generating at least one orthogonal projection matrix.
摘要:
This disclosure describes an integrated framework for class-unsupervised object segmentation. The class-unsupervised object segmentation occurs by integrating top-down constraints and bottom-up constraints on object shapes using an algorithm in an integrated manner. The algorithm describes a relationship among object parts and superpixels. This process forms object shapes with object parts and oversegments pixel images into the superpixels, with the algorithm in conjunction with the constraints. This disclosure describes computing a mask map from a hybrid graph, segmenting the image into a foreground object and a background, and displaying the foreground object from the background.
摘要:
A method for modeling data affinities and data structures. In one implementation, a contextual distance may be calculated between a selected data point in a data sample and a data point in a contextual set of the selected data point. The contextual set may include the selected data point and one or more data points in the neighborhood of the selected data point. The contextual distance may be the difference between the selected data point's contribution to the integrity of the geometric structure of the contextual set and the data point's contribution to the integrity of the geometric structure of the contextual set. The process may be repeated for each data point in the contextual set of the selected data point. The process may be repeated for each selected data point in the data sample. A digraph may be created using a plurality of contextual distances generated by the process.
摘要:
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.
摘要:
Directed graph embedding is described. In one implementation, a system explores the link structure of a directed graph and embeds the vertices of the directed graph into a vector space while preserving affinities that are present among vertices of the directed graph. Such an embedded vector space facilitates general data analysis of the information in the directed graph. Optimal embedding can be achieved by measuring local affinities among vertices via transition probabilities between the vertices, based on a stationary distribution of Markov random walks through the directed graph. For classifying linked web pages represented by a directed graph, the system can train a support vector machine (SVM) classifier, which can operate in a user-selectable number of dimensions.
摘要:
A search includes comparing a query image provided by a user to a plurality of stored images of faces stored in a stored image database, and determining a similarity of the query image to the plurality of stored images. One or more resultant images of faces, selected from among the stored images, are displayed to the user based on the determined similarity of the stored images to the query image provided by the user. The resultant images are displayed based at least in part on one or more facial features.
摘要:
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.
摘要:
Described is a technology in which images initially ranked by some relevance estimate (e.g., according to text-based similarities) are re-ranked according to visual similarity with a user-selected image. A user-selected image is received and classified into an intention class, such as a scenery class, portrait class, and so forth. The intention class is used to determine how visual features of other images compare with visual features of the user-selected image. For example, the comparing operation may use different feature weighting depending on which intention class was determined for the user-selected image. The other images are re-ranked based upon their computed similarity to the user-selected image, and returned as query results. Retuning of the feature weights using actual user-provided relevance feedback is also described.