Abstract: Technologies that enable correcting for the non-linear relationship between scene irradiance and digital pixel intensity values of an image of the scene produced by a camera. Imaging noise is used as a signal from which a corrective function is derived. Noise distributions from the image are evaluated to determine the radiometric response function of the camera, from which an inverse response function is computed and used for calibration.

Abstract: Technologies that enable correcting for the non-linear relationship between scene irradiance and digital pixel intensity values of an image of the scene produced by a camera. Imaging noise is used as a signal from which a corrective function is derived. Noise distributions from the image are evaluated to determine the radiometric response function of the camera, from which an inverse response function is computed and used for calibration.

Abstract: Technologies that enable correcting for the non-linear relationship between scene irradiance and digital pixel intensity values of an image of the scene produced by a camera. Imaging noise is used as a signal from which a corrective function is derived. Noise distributions from the image are evaluated to determine the radiometric response function of the camera, from which an inverse response function is computed and used for calibration.

Abstract: Technologies that enable correcting for the non-linear relationship between scene irradiance and digital pixel intensity values of an image of the scene produced by a camera. Imaging noise is used as a signal from which a corrective function is derived. Noise distributions from the image are evaluated to determine the radiometric response function of the camera, from which an inverse response function is computed and used for calibration.

Abstract: Technologies for comparing observed intensities using a probabilistic similarity measure. In the probabilistic similarity measure example, there is no attempt to estimate a true intensity. Rather, the similarity of two observed intensities is defined as the likelihood that they each resulted from the same but unknown true identity while taking into account the noise characteristics of the camera observing the intensities. Since the true intensity is unknown, all possible true intensities are taken into account, rather than using a specific true intensity estimate. The probabilistic similarity measure indicates the degree to which two intensities correspond to the same intensity without estimating a true scene intensity value.

Abstract: Technologies that enable correcting for the non-linear relationship between scene irradiance and digital pixel intensity values of an image of the scene produced by a camera. Imaging noise is used as a signal from which a corrective function is derived. Noise distributions from the image are evaluated to determine the radiometric response function of the camera, from which an inverse response function is computed and used for calibration.

Abstract: A real-time algorithm for rendering of an inhomogeneous scattering media such as smoke under dynamic low-frequency environment lighting is described. An input media animation is represented as a sequence of density fields, each of which is decomposed into a weighted sum of a set of radial basis functions (RBFs) and an optional residual field. Source radiances from single and optionally multiple scattering are directly computed at only the RBF centers and then approximated at other points in the volume using an RBF-based interpolation. Unique approximation techniques are introduced in the computational algorithms to simplify and speed up the computation of source radiance contributed by single and multiple scattering. Using the computed source radiances, a ray marching technique using slice-based integration of radiance along each viewing ray may be performed to render the final image.

Abstract: Technologies that enable correcting for the non-linear relationship between scene irradiance and digital pixel intensity values of an image of the scene produced by a camera. Imaging noise is used as a signal from which a corrective function is derived. Noise distributions from the image are evaluated to determine the radiometric response function of the camera, from which an inverse response function is computed and used for calibration.

Abstract: A real-time algorithm for rendering of an inhomogeneous scattering media such as smoke under dynamic low-frequency environment lighting is described. An input media animation is represented as a sequence of density fields, each of which is decomposed into a weighted sum of a set of radial basis functions (RBFs) and an optional residual field. Source radiances from single and optionally multiple scattering are directly computed at only the RBF centers and then approximated at other points in the volume using an RBF-based interpolation. Unique approximation techniques are introduced in the computational algorithms to simplify and speed up the computation of source radiance contributed by single and multiple scattering. Using the computed source radiances, a ray marching technique using slice-based integration of radiance along each viewing ray may be performed to render the final image.

Abstract: A real-time algorithm for rendering of an inhomogeneous scattering media such as smoke under dynamic low-frequency environment lighting is described. An input media animation is represented as a sequence of density fields, each of which is decompressed into a weighted sum of a set of radial basis functions (RBFs) and an optional residual field. Source radiances from single and optionally multiple scattering are directly computed at only the RBF centers and then approximated at other points in the volume using an RBF-based interpolation. Using the computed source radiances, a ray marching technique using slice-based integration of radiance along each viewing ray is performed to render the final image. During the ray marching process, the residual field may be compensated back into the radiance integral to generate images of higher detail.

Abstract: A real-time algorithm for rendering of an inhomogeneous scattering media such as smoke under dynamic low-frequency environment lighting is described. An input media animation is represented as a sequence of density fields, each of which is represented by an approximate model density field and a residual density field. The algorithm uses the approximate model density field to compute an approximate source radiance, and further computes an effective exitant radiance by compositing the approximate source radiance using a compositing methods such as ray marching. During the compositing process (e.g., ray marching), the residual field is compensated back into the radiance integral to generate images of higher detail.

Abstract: Technologies for comparing observed intensities using a probabilistic similarity measure. In the probabilistic similarity measure example, there is no attempt to estimate a true intensity. Rather, the similarity of two observed intensities is defined as the likelihood that they each resulted from the same but unknown true identity while taking into account the noise characteristics of the camera observing the intensities. Since the true intensity is unknown, all possible true intensities are taken into account, rather than using a specific true intensity estimate. The probabilistic similarity measure indicates the degree to which two intensities correspond to the same intensity without estimating a true scene intensity value.

Abstract: Technologies that enable correcting for the non-linear relationship between scene irradiance and digital pixel intensity values of an image of the scene produced by a camera. Imaging noise is used as a signal from which a corrective function is derived. Noise distributions from the image are evaluated to determine the radiometric response function of the camera, from which an inverse response function is computed and used for calibration.

Abstract: A real-time algorithm for rendering of an inhomogeneous scattering media such as smoke under dynamic low-frequency environment lighting is described. An input media animation is represented as a sequence of density fields, each of which is decomposed into a weighted sum of a set of radial basis functions (RBFs) and an optional residual field. Source radiances from single and optionally multiple scattering are directly computed at only the RBF centers and then approximated at other points in the volume using an RBF-based interpolation. Unique approximation techniques are introduced in the computational algorithms to simplify and speed up the computation of source radiance contributed by single and multiple scattering. Using the computed source radiances, a ray marching technique using slice-based integration of radiance along each viewing ray may be performed to render the final image.

Abstract: A real-time algorithm for rendering of an inhomogeneous scattering media such as smoke under dynamic low-frequency environment lighting is described. An input media animation is represented as a sequence of density fields, each of which is decompressed into a weighted sum of a set of radial basis functions (RBFs) and an optional residual field. Source radiances from single and optionally multiple scattering are directly computed at only the RBF centers and then approximated at other points in the volume using an RBF-based interpolation. Using the computed source radiances, a ray marching technique using slice-based integration of radiance along each viewing ray is performed to render the final image. During the ray marching process, the residual field may be compensated back into the radiance integral to generate images of higher detail.

Abstract: A real-time algorithm for rendering of an inhomogeneous scattering media such as smoke under dynamic low-frequency environment lighting is described. An input media animation is represented as a sequence of density fields, each of which is represented by an approximate model density field and a residual density field. The algorithm uses the approximate model density field to compute an approximate source radiance, and further computes an effective exitant radiance by compositing the approximate source radiance using a compositing methods such as ray marching. During the compositing process (e.g., ray marching), the residual field is compensated back into the radiance integral to generate images of higher detail.

Abstract: A novel method for synchronizing the lips of a sketched face to an input voice. The lip synchronization system and method approach is to use training video as much as possible when the input voice is similar to the training voice sequences. Initially, face sequences are clustered from video segments, then by making use of sub-sequence Hidden Markov Models, a correlation between speech signals and face shape sequences is built. From this re-use of video, the discontinuity between two consecutive output faces is decreased and accurate and realistic synthesized animations are obtained. The lip synchronization system and method can synthesize faces from input audio in real-time without noticeable delay. Since acoustic feature data calculated from audio is directly used to drive the system without considering its phonemic representation, the method can adapt to any kind of voice, language or sound.

Abstract: A novel method for synchronizing the lips of a sketched face to an input voice. The lip synchronization system and method approach is to use training video as much as possible when the input voice is similar to the training voice sequences. Initially, face sequences are clustered from video segments, then by making use of sub-sequence Hidden Markov Models, a correlation between speech signals and face shape sequences is built. From this re-use of video, the discontinuity between two consecutive output faces is decreased and accurate and realistic synthesized animations are obtained. The lip synchronization system and method can synthesize faces from input audio in real-time without noticeable delay. Since acoustic feature data calculated from audio is directly used to drive the system without considering its phonemic representation, the method can adapt to any kind of voice, language or sound.

Abstract: A novel method for synchronizing the lips of a sketched face to an input voice. The lip synchronization system and method approach is to use training video as much as possible when the input voice is similar to the training voice sequences. Initially, face sequences are clustered from video segments, then by making use of sub-sequence Hidden Markov Models, a correlation between speech signals and face shape sequences is built. From this re-use of video, the discontinuity between two consecutive output faces is decreased and accurate and realistic synthesized animations are obtained. The lip synchronization system and method can synthesize faces from input audio in real-time without noticeable delay. Since acoustic feature data calculated from audio is directly used to drive the system without considering its phonemic representation, the method can adapt to any kind of voice, language or sound.