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:
Real-time rendering of realistic rain is described. In one aspect, image samples of real rain and associated information are automatically modeled in real-time to generate synthetic rain particles in view of respective scene radiances of target video content frames. The synthetic rain particles are rendered in real-time using pre-computed radiance transfer with uniform random distribution across respective frames of the target video content.
摘要:
Embodiments of the invention determine whether an image has been altered. Sets of patches are selected in the image, and corresponding inverse response functions are provided to a support vector machine (SVM). The support vector machine is trained with exemplary normal and abnormal inverse response functions. Once trained, the support vector machine analyzes inverse response functions corresponding to a suspected image. The support vector machine determines if the inverse response functions are normal or abnormal by analyzing a set of features. In one embodiment, features include measures for monotonic characteristics, fluctuation characteristics, and divergence characteristics of the red, green, and blue components of a tuple. Each tuple of inverse response functions is associated with a set of patches selected in the image.
摘要:
Systems and methods perform Laplacian Principal Components Analysis (LPCA). In one implementation, an exemplary system receives multidimensional data and reduces dimensionality of the data by locally optimizing a scatter of each local sample of the data. The optimization includes summing weighted distances between low dimensional representations of the data and a mean. The weights of the distances can be determined by a coding length of each local data sample. The system can globally align the locally optimized weighted scatters of the local samples and provide a global projection matrix. The LPCA improves performance of such applications as face recognition and manifold learning.
摘要:
Real-time rendering of realistic rain is described. In one aspect, image samples of real rain and associated information are automatically modeled in real-time to generate synthetic rain particles in view of respective scene radiances of target video content frames. The synthetic rain particles are rendered in real-time using pre-computed radiance transfer with uniform random distribution across respective frames of the target video content.
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:
A strategy is described for producing an animated scene from multiple high resolution still images. The strategy involves: creating a graph based on an analysis of similarity among the plural still images; performing partial temporal order recovery to define a partial ordering among the plural still images; and extracting an output sequence from the plural still images using second-order Markov Chain analysis, using the partial ordering as a reference. The strategy can perform the above-described analysis with respect to multiple independent animated regions (IARs) within the still images. Further, the strategy can decompose any IAR with a significant amount of motion into multiple semi-independent animated regions (SIARs). The SIARs are defined to be weakly interdependent.
摘要:
Embodiments of the invention determine whether an image has been altered. Sets of patches are selected in the image, and corresponding inverse response functions are provided to a support vector machine (SVM). The support vector machine is trained with exemplary normal and abnormal inverse response functions. Once trained, the support vector machine analyzes inverse response functions corresponding to a suspected image. The support vector machine determines if the inverse response functions are normal or abnormal by analyzing a set of features. In one embodiment, features include measures for monotonic characteristics, fluctuation characteristics, and divergence characteristics of the red, green, and blue components of a tuple. Each tuple of inverse response functions is associated with a set of patches selected in the image.
摘要:
A strategy is described for producing an animated scene from multiple high resolution still images. The strategy involves: creating a graph based on an analysis of similarity among the plural still images; performing partial temporal order recovery to define a partial ordering among the plural still images; and extracting an output sequence from the plural still images using second-order Markov Chain analysis, using the partial ordering as a reference. The strategy can perform the above-described analysis with respect to multiple independent animated regions (IARs) within the still images. Further, the strategy can decompose any IAR with a significant amount of motion into multiple semi-independent animated regions (SIARs). The SIARs are defined to be weakly interdependent.
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.