Abstract: A digital camera having a single image sensor made up of an array of filtered photosites used to capture non-visible light wavelengths in addition to the standard red/green/blue (RGB) or other visible light intensity values is presented. Essentially, this is accomplished using a separate filter disposed over each photosite that exhibits a light transmission function with regard to wavelength which passes only a prescribed range of wavelengths—some passing light in the visible light spectrum and others in the non-visible light spectrum. The photosites passing non-visible light wavelengths can be configured to pass light in the infrared (IR) light spectrum, which can be limited to just the near infrared (NIR) spectrum if desired, or alternately light in the ultra-violet (UV) light spectrum.

Abstract: The system provides improved procedures to estimate head motion between two images of a face. Locations of a number of distinct facial features are identified in two images. The identified locations can correspond to the eye comers, mouth corners and nose tip. The locations are converted into as a set of physical face parameters based on the symmetry of the identified distinct facial features. The set of physical parameters reduces the number of unknowns as compared to the number of equations used to determine the unknowns. An initial head motion estimate is determined by: (a) estimating each of the set of physical parameters, (b) estimating a first head pose transform corresponding to the first image, and (c) estimating a second head pose transform corresponding to the second image. The head motion estimate can be incorporated into a feature matching algorithm to refine the head motion estimation and the physical facial parameters.

Abstract: A system and method, called Image-Based Surface Detail Transfer, to transfer geometric details from one surface of an object in an image to another with simple 2D image operations. The basic observation is that, without knowing its 3D geometry, geometric details (local deformations) can be extracted from a single image of an object in a way independent of its surface reflectance, and furthermore, these geometric details can be transferred to modify the appearance of other objects directly in images. Examples are shown including surface detail transfer between real objects, as well as between real and synthesized objects.

Abstract: An incremental motion estimation system and process for estimating the camera pose parameters associated with each image of a long image sequence. Unlike previous approaches, which rely on point matches across three or more views, the present system and process also includes those points shared only by two views. The problem is formulated as a series of localized bundle adjustments in such a way that the estimated camera motions in the whole sequence are consistent with each other. The result of the inclusion of two-view matching points and the localized bundle adjustment approach is more accurate estimates of the camera pose parameters for each image in the sequence than previous incremental techniques, and providing an accuracy approaching that of global bundle adjustment techniques except with processing times about 100 to 700 times faster than the global approaches.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: An incremental motion estimation system and process for estimating the camera pose parameters associated with each image of a long image sequence. Unlike previous approaches, which rely on point matches across three or more views, the present system and process also includes those points shared only by two views. The problem is formulated as a series of localized bundle adjustments in such a way that the estimated camera motions in the whole sequence are consistent with each other. The result of the inclusion of two-view matching points and the localized bundle adjustment approach is more accurate estimates of the camera pose parameters for each image in the sequence than previous incremental techniques, and providing an accuracy approaching that of global bundle adjustment techniques except with processing times about 100 to 700 times faster than the global approaches.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: A system and process for improving the appearance of improperly colored and/or improperly exposed images is presented. This involves the use of two novel techniques—namely an automatic color correction technique and an automatic exposure correction technique. The automatic color correction technique takes information from within an image to determine true color characteristics, and improves the color in improperly colored pixels. The automatic exposure correction technique measures the average intensity of all of the pixels and adjusts the entire image pixel by pixel to compensate for over or under exposure. These techniques are stand alone in that each can be applied to an image exclusive of the other, or they can both be applied in any order desired.

Abstract: A system and process for improving the appearance of improperly colored and/or improperly exposed images is presented. This involves the use of two novel techniques—namely an automatic color correction technique and an automatic exposure correction technique. The automatic color correction technique takes information from within an image to determine true color characteristics, and improves the color in improperly colored pixels. The automatic exposure correction technique measures the average intensity of all of the pixels and adjusts the entire image pixel by pixel to compensate for over or under exposure. These techniques are stand alone in that each can be applied to an image exclusive of the other, or they can both be applied in any order desired.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: Described herein is a technique for creating a 3D face model using images obtained from an inexpensive camera associated with a general-purpose computer. Two still images of the user are captured, and two video sequences. The user is asked to identify five facial features, which are used to calculate a mask and to perform fitting operations. Based on a comparison of the still images, deformation vectors are applied to a neutral face model to create the 3D model. The video sequences are used to create a texture map. The process of creating the texture map references the previously obtained 3D model to determine poses of the sequential video images.

Abstract: A mobile device is provided that includes a digit input that can be manipulated by a user's fingers or thumb, an air conduction microphone and an alternative sensor that provides an alternative sensor signal indicative of speech. Under some embodiments, the mobile device also includes a proximity sensor that provides a proximity signal indicative of the distance from the mobile device to an object. Under some embodiments, the signal from the air conduction microphone, the alternative sensor signal, and the proximity signal are used to form an estimate of a clean speech value. In further embodiments, a sound is produced through a speaker in the mobile device based on the amount of noise in the clean speech value. In other embodiments, the sound produced through the speaker is based on the proximity sensor signal.

Abstract: A system and method, called Image-Based Surface Detail Transfer, to transfer geometric details from one surface of an object in an image to another with simple 2D image operations. The basic observation is that, without knowing its 3D geometry, geometric details (local deformations) can be extracted from a single image of an object in a way independent of its surface reflectance, and furthermore, these geometric details can be transferred to modify the appearance of other objects directly in images. Examples are shown including surface detail transfer between real objects, as well as between real and synthesized objects.

Abstract: A system and method for transmitting a clear image of a whiteboard work surface for remote collaboration. The image is separated into two portions; the projected image of the work surface, and the writing physically added to the whiteboard by participants. This separation allows several benefits. The bandwidth requirements are much lower than video teleconferencing, and the benefits of whiteboard sharing are improved. The visual echo created on a physical whiteboard can be canceled.

Abstract: A real-time approximately 360 degree image correction system and a method for alleviating distortion and perception problems in images captured by omni-directional cameras. In general, the real-time panoramic image correction method generates a warp table from pixel coordinates of a panoramic image and applies the warp table to the panoramic image to create a corrected panoramic image. The corrections are performed using a parametric class of warping functions that include Spatially Varying Uniform (SVU) scaling functions. The SVU scaling functions and scaling factors are used to perform vertical scaling and horizontal scaling on the panoramic image pixel coordinates. A horizontal distortion correction is performed using the SVU scaling functions at at least two different scaling factors. This processing generates a warp table that can be applied to the panoramic image to yield the corrected panoramic image.

Abstract: A method and a system for progressive stereo matching of digital images representing a scene. In general, the present invention uses a progressive iterative technique that includes a disparity gradient limit principle and a least commitment strategy. The progressive iterative technique finds generally unambiguous pixel matches by beginning with a few reliable pixel matches and finding progressively more unambiguous pixel matches. Unambiguous pixel matches found in the previous iteration are used to define the search ranges for each pixel to guide matching in the current iteration. Unambiguous pixel matches in the current iteration then are found using a novel correlation technique and based on a correlation score associated with a pixel match. The search range is capable of being rotated, and is part of a novel correlation technique of the present invention that provides a more robust estimate of pixel match reliability.

Abstract: A method and a system for progressive stereo matching of digital images representing a scene. In general, the present invention uses a progressive iterative technique that includes a disparity gradient limit principle and a least commitment strategy. Generally unambiguous pixel matches are found by beginning with a few reliable pixel matches and finding progressively more unambiguous pixel matches. Unambiguous pixel matches are used to define the search ranges for each pixel to guide matching in the current iteration. Unambiguous pixel matches then are found using a novel correlation technique and based on a correlation score associated with a pixel match. The search range is capable of being rotated, and is part of a novel correlation technique that provides a more robust estimate of pixel match reliability. Potential pixel matches found in the search ranges are tested for ambiguity and unambiguous matches are selected and added to the reliable pixel matches.