Abstract: In exemplary implementations of this invention, a depth-sensing system includes multiple light sources, multiple cameras, a pattern generator and one or more computers. The system measures depth in a scene. The multiple light sources emit light that illuminates a pattern generator. The pattern generator refracts, reflects or selectively attenuates the light, to create a textured light pattern that is projected onto the scene. The multiple cameras capture images of the scene from different viewpoints, while the scene is illuminated by the textured light. One or more computers process the images and compute the depth of points in the scene, by a computation that involves stereoscopic triangulation.

Abstract: A system for estimating a photoplethysmogram waveform of a target includes an image processor configured to obtain images of the target and a waveform analyzer. The waveform analyzer is configured to determine a weight of a portion of the target. The weight is based on a time variation of a light reflectivity of the portion of the target. The time variation of the light reflectivity of the target is based on the images. The waveform analyzer is further configured to estimate a PPG waveform of the target based on the weight of the portion and the time variation of the light reflectivity of the portion.

Abstract: Provided is an image processing apparatus including an image generation unit that, from photographic images that are captured using multiple photographic parameters, generates an image of which values of the multiple photographic parameters are different from values of the photographic image.

Abstract: A set of images is acquired of a scene by a camera. The scene includes a moving object, and a relative difference of a motion of the camera and a motion of the object is substantially zero. Statistical properties of pixels in the images are determined, and a statistical method is applied to the statistical properties to identify pixels corresponding to the object.

Abstract: Depth values in a scene are measured by projecting sets of patterns on the scene, wherein each set of patterns is structured with different spatial frequency using different encoding functions. Sets of images of the scene is acquired, wherein there is one image for each pattern in each set. Depth values are determining for each pixel at corresponding locations in the sets of images. The depth values of each pixel are analyzed, and the depth value is returned if the depth values at the corresponding locations are similar. Otherwise, the depth value is marked as having an error.

Abstract: A dynamic scene is reconstructed as depths and an extended depth of field video by first acquiring, with a camera including a lens and sensor, a focal stack of the dynamic scene while changing a focal depth. An optical flow between the frames of the focal stack is determined, and the frames are warped according to the optical flow to align the frames and to generate a virtual static focal stack. Finally, a depth map and a texture map for each virtual static focal stack is generated using a depth from defocus, wherein the texture map corresponds to an EDOF image.

Abstract: A camera for acquiring a sequence of frames of a scene as a video includes a sensor with an array of sensor pixels. Individual sensor pixels are modulated by corresponding modulation functions while acquiring each frame of the video. The modulation can be performed by a transmissive or reflective masked arranged in an optical path between the scene and the senor. The frames can be reconstructed to have a frame rate and spatial resolution substantially higher than a natural frame rate and a spatial resolution of the camera.

Abstract: A dynamic scene is reconstructed as depths and an extended depth of field video by first acquiring, with a camera including a lens and sensor, a focal stack of the dynamic scene while changing a focal depth. An optical flow between the frames of the focal stack is determined, and the frames are warped according to the optical flow to align the frames and to generate a virtual static focal stack. Finally, a depth map and a texture map for each virtual static focal stack is generated using a depth from defocus, wherein the texture map corresponds to an EDOF image.

Abstract: A system for measuring a position includes a scale pattern encoding the position with a first resolution; a sensor for acquiring an input signal representing a portion of the scale pattern, the portion encoding a codeword shifted with a shift; and a processor for comparing the input signal with a model signal of the codeword to determine the shift, and to determine the position based on the codeword and the shift.

Abstract: A pose for an object in a scene is determined by first rendering sets of virtual images of a model of the object using a virtual camera. Each set of virtual images is for a different known pose the model, and constructing virtual depth edge map from each virtual image, which are stored in a database. A set of real images of the object at an unknown pose are acquired by a real camera, and constructing real depth edge map for each real image. The real depth edge maps are compared with the virtual depth edge maps using a cost function to determine the known pose that best matches the unknown pose, wherein the matching is based on locations and orientations of pixels in the depth edge maps.

Abstract: Embodiments of the invention disclose a system and a method for generating an output video having a first temporal resolution from input videos acquired synchronously of a scene by at least three cameras, wherein each input video has a second temporal resolution, wherein the second temporal resolution is less than the first temporal resolution. The method obtains frames of each input video, wherein the frames are sampled according to a code selected such that an integration time of the corresponding camera is greater than a frame time of the output video. Next, the method combines intensities of pixels of corresponding frames in a linear system; and solves the linear system independently for each corresponding frame to generate the output video.

Abstract: Depth values in a scene are measured by projecting sets of patterns on the scene, wherein each set of patterns is structured with different spatial frequency using different encoding functions. Sets of images of the scene is acquired, wherein there is one image for each pattern in each set. Depth values are determining for each pixel at corresponding locations in the sets of images. The depth values of each pixel are analyzed, and the depth value is returned if the depth values at the corresponding locations are similar. Otherwise, the depth value is marked as having an error.

Abstract: A point correspondence procedure is applied to a set of images of a specular object to produce sparse reflection correspondences. The set of images is subject to rotation while acquired by a camera. That is, either the camera, the environment or the object rotates. Either a linear system A?=0 is solved or a related second order cone program (SOCP) is solved, where ? is a vector of local surface parameters. Gradients of the surface are obtained from the local quadric surface parameters, and the gradients are integrated to obtain normals, wherein the normals define a shape of the surface.

Abstract: A camera includes a lens and a sensor. A dynamic mask is arranged at an aperture plane between the lens and the sensor, and a static mask is arranged immediately adjacent to the sensor. Angular, temporal or spatial variations in light rays acquired of a scene by the sensor are mapped to individual pixels of the sensor.

Abstract: A camera for acquiring a sequence of frames of a scene as a video includes a sensor with an array of sensor pixels. Individual sensor pixels are modulated by corresponding modulation functions while acquiring each frame of the video. The modulation can be performed by a transmissive or reflective masked arranged in an optical path between the scene and the senor. The frames can be reconstructed to have a frame rate and spatial resolution substantially higher than a natural frame rate and a spatial resolution of the camera.

Abstract: A pose of an object is determine by acquiring sets of images of the object by a camera, wherein the object has a thread arranged on a surface such that a local region of the object appears substantially spherical, wherein the camera is at a different point of view for each set, and wherein each image in each set is acquired while the scene is illuminated from a different direction. A set of features is extracted from each image, wherein the features correspond to points on the surface having normals towards the camera. A parametric line is fitted to the points for each image, wherein the line lies on a plane joining a center of the camera and an axis of the object. Then, geometric constraints are applied to lines to determine the pose of the object.

Abstract: Embodiments of the invention disclose a system and a method for determining points of parabolic curvature on a surface of a specular object from a set of images of the object is acquired by a camera under a relative motion between a camera-object pair and the environment. The method determines directions of image gradients at each pixel of each image in the set of images, wherein pixels from different images corresponding to an identical point on the surface of the object form corresponding pixels. The corresponding pixels having substantially constant the direction of the image gradients are selected as pixels representing points of the parabolic curvature.

Abstract: Embodiments of the invention disclose a system and a method for generating an output video having a first temporal resolution from input videos acquired synchronously of a scene by at least three cameras, wherein each input video has a second temporal resolution, wherein the second temporal resolution is less than the first temporal resolution. The method obtains frames of each input video, wherein the frames are sampled according to a code selected such that an integration time of the corresponding camera is greater than a frame time of the output video. Next, the method combines intensities of pixels of corresponding frames in a linear system; and solves the linear system independently for each corresponding frame to generate the output video.

Abstract: A sequence of images of a scene having varying spatio-temporal resolutions is acquired by a sensor of a camera. Adjacent pixels of the sensor are partitioned into a multiple sets of the pixels. An integration time for acquiring each set of pixels is partitioned into multiple time intervals. The images are acquired while some of the pixels in each set are ON for some of the intervals, while other pixels are OFF. Then, the pixels are combined into a space-time volume of voxels, wherein the voxels have varying spatial resolutions and varying temporal resolutions.

Abstract: Embodiments of the invention disclose a system and a method for determining points of parabolic curvature on a surface of a specular object from a set of images of the object is acquired by a camera under a relative motion between a camera-object pair and the environment. The method determines directions of image gradients at each pixel of each image in the set of images, wherein pixels from different images corresponding to an identical point on the surface of the object form corresponding pixels. The corresponding pixels having substantially constant the direction of the image gradients are selected as pixels representing points of the parabolic curvature.