Abstract: Arrangements (e.g., apparatus, system, method, article of manufacture) for reconstructing a depth image of a scene. Some embodiments include: a processor; and a non-transitory computer readable medium to store a set of instructions for execution by the processor, the set of instructions to cause the processor to perform various operations. Operations include: collecting multiple data sets for a code-modulated light pulse reflected from an object in a scene, with each data set associated with a direction in a set of directions for the reflected code-modulated light pulse; assigning a fitness value to each data set based on one or more parameters of a model; and reconstructing a depth image providing a depth at each direction based on a corresponding data set and fitness value, the depth to correspond with a round-trip delay time of the code-modulated light pulse.

Abstract: An example apparatus for calibrating texture cameras includes an image receiver to receive a depth image from a depth camera and a color image from a texture camera. The apparatus also includes a feature extractor to extract features from the depth image and the color image. The apparatus further includes a feature tester to detect that the extracted features from the depth image and the color image exceed a quality threshold. The apparatus includes a misalignment detector to detect a misalignment between the extracted features from depth image and the extracted features from color image exceeds a misalignment threshold. The apparatus also further includes a calibrator to modify calibration parameters for the texture camera to reduce the detected misalignment between the extracted features from the depth image and the extracted features from the color image below a misalignment threshold.

Abstract: In accordance with disclosed embodiments, there is described a depth camera calibration system which includes: a depth camera to be calibrated; a calibration application to execute upon a mobile device, the calibration application to: (i) determine a precise image size of a calibration image to be displayed to a screen of the mobile device based on a screen size of the mobile device, the calibration image having embedded therein a plurality of objects of a known size, (ii) encode the known size of the objects into an optical machine-readable data representation, and (iii) display the encoded optical machine-readable data representation to the mobile device; in which the depth camera is to read the optical machine-readable data representation displayed by the mobile device to determine the known size of the objects of the calibration image; in which the calibration application is to display the calibration image to the mobile device; and in which an imager of the depth camera is to capture the objects of the c

Abstract: A method and apparatus for performing a single view depth and texture calibration are described. In one embodiment, the apparatus comprises a calibration unit operable to perform a single view calibration process using a captured single view a target having a plurality of plane geometries having detectable features and being at a single orientation and to generate calibration parameters to calibrate one or more of the projector and multiple cameras using the single view of the target.

Abstract: A method and apparatus for performing temperature compensation for thermal distortions in a camera system. In one embodiment, the system comprises a first camera configured to capture a sequence of images of the object; a second device; a processing unit to receive the sequence of images and determine depth information in response to parameters of the camera and the second device; one or more temperature sensors; and a thermal correction unit responsive to temperature information from the one or more temperature sensors to adjust one or more of the calibration parameters of the first camera and the second device.

Abstract: In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing maximum likelihood image binarization in a coded light range camera.

Abstract: A mechanism is described for facilitating depth image dequantization at computing devices according to one embodiment. A method of embodiments, as described herein, includes detecting a digital image of an object, the digital image including pixels having associated pixel values contaminated by noise, and side information pertaining to confidence of a value acquired in each pixel. The method may further include measuring characteristics of noise in each pixel of the digital image, and a plurality of weights relating to one or more of the pixel values, the side information, and the noise characteristics. The method may further include computing a smart filter based on a combination of the plurality of weights, applying the smart filter to filter the digital image by reducing the noise in the digital image, and outputting the filtered digital image.

Abstract: A method and apparatus for auto range control are described. In one embodiment, the apparatus comprises a projector configured to project a sequence of light patterns on an object; a first camera configured to capture a sequence of images of the object illuminated with the projected light patterns; a controller coupled to the projector and first camera and operable to receive the sequence of images and perform range control by controlling power of the sequence of light patterns being projected on the object and exposure time of a camera based on information obtained from the sequence of images captured by the camera.

Abstract: A method and apparatus for performing a single view depth and texture calibration are described. In one embodiment, the apparatus comprises a calibration unit operable to perform a single view calibration process using a captured single view a target having a plurality of plane geometries having detectable features and being at a single orientation and to generate calibration parameters to calibrate one or more of the projector and multiple cameras using the single view of the target.

Abstract: A mechanism is described for facilitating three-dimensional (3D) depth imaging systems, and morphological and geometric filters for edge enhancement in depth images at computing devices according to one embodiment. A method of embodiments, as described herein, includes detecting an input digital image of an object, the digital image comprising data pixels contaminated by noise and confidence values corresponding to the data pixels, and computing a morphological filter by matching the confidence pixels in the input digital image with a set of matching templates, and using a set of masking templates to determine the data pixels and confidence pixels in the filtered image. The method further include computing an edge filter by performing computation of distances between the data pixels along a plurality of directions to determine an edge direction, and determining the data pixels and and the confidence pixels in a filtered image based on the edge direction.

Abstract: A method and apparatus for projector distortion compensation in structured light depth reconstruction are described. In one embodiment, the apparatus comprises a projector configured to project a sequence of light patterns on an object; a first camera configured to capture a sequence of images of the object illuminated with the projected light patterns; a processing unit to receive the sequence of images and reconstruct depth using triangulation in response to camera and projector location coordinates; and a projector distortion compensation unit operable to generate a new projector location coordinate in response to an observed distorted projector location coordinate, the projector distortion compensation unit to provide the new projector location coordinate to the processing unit for use in generating depth values via triangulation.

Abstract: A method and apparatus for performing temperature compensation for thermal distortions in a camera system. In one embodiment, the system comprises a first camera configured to capture a sequence of images of the object; a second device; a processing unit to receive the sequence of images and determine depth information in response to parameters of the camera and the second device; one or more temperature sensors; and a thermal correction unit responsive to temperature information from the one or more temperature sensors to adjust one or more of the calibration parameters of the first camera and the second device.

Abstract: A method and apparatus for auto range control are described. In one embodiment, the apparatus comprises a projector configured to project a sequence of light patterns on an object; a first camera configured to capture a sequence of images of the object illuminated with the projected light patterns; a controller coupled to the projector and first camera and operable to receive the sequence of images and perform range control by controlling power of the sequence of light patterns being projected on the object and exposure time of a camera based on information obtained from the sequence of images captured by the camera.

Abstract: A method and apparatus for performing a single view depth and texture calibration are described. In one embodiment, the apparatus comprises a calibration unit operable to perform a single view calibration process using a captured single view a target having a plurality of plane geometries having detectable features and being at a single orientation and to generate calibration parameters to calibrate one or more of the projector and multiple cameras using the single view of the target.

Abstract: A mechanism is described for facilitating management of image noise in digital images using a smart noise management filter according to one embodiment. A method of embodiments, as described herein, includes detecting a digital image of an object, where detecting further includes detecting a pattern signal associated with the digital image. The method may further include measuring a spread function relating to at least one of the digital image and an imaging system of a computing device, where measuring further includes determining deconvolution of the spread function, and where measuring further includes computing a pre-shaping filter based on the deconvolution of the spread function. The method may further include executing the pre-shaping filter to apply the pattern signal to the deconvolution of the spread function to obtain a pre-shaped projection pattern of the digital image.

Abstract: A mechanism is described for facilitating code filters for coded light depth acquisition in depth images at computing devices according to one embodiment. A method of embodiments, as described herein, includes detecting a code image of an object comprising pixels of code values and pixels of metadata values including confidence and code transition locations, and computing a vertical filter to be applied to the code image to smooth out the code transitions along vertical directions. The method further include computing a horizontal filter to be applied to the code image to smooth out the code transitions along horizontal directions, and computing a consistency filter to be applied to the code image to increase an accuracy of the code values and mark inconsistent pixels as invalid.

Abstract: A mechanism is described for facilitating three-dimensional (3D) depth imaging systems, and morphological and geometric filters for edge enhancement in depth images at computing devices according to one embodiment. A method of embodiments, as described herein, includes detecting an input digital image of an object, the digital image comprising data pixels contaminated by noise and confidence values corresponding to the data pixels, and computing a morphological filter by matching the confidence pixels in the input digital image with a set of matching templates, and using a set of masking templates to determine the data pixels and confidence pixels in the filtered image. The method further include computing an edge filter by performing computation of distances between the data pixels along a plurality of directions to determine an edge direction, and determining the data pixels and and the confidence pixels in a filtered image based on the edge direction.

Abstract: A method and apparatus for auto range control are described. In one embodiment, the apparatus comprises a projector configured to project a sequence of light patterns on an object; a first camera configured to capture a sequence of images of the object illuminated with the projected light patterns; a controller coupled to the projector and first camera and operable to receive the sequence of images and perform range control by controlling power of the sequence of light patterns being projected on the object and exposure time of a camera based on information obtained from the sequence of images captured by the camera.

Abstract: A mechanism is described for facilitating code filters for coded light depth acquisition in depth images at computing devices according to one embodiment. A method of embodiments, as described herein, includes detecting a code image of an object comprising pixels of code values and pixels of metadata values including confidence and code transition locations, and computing a vertical filter to be applied to the code image to smooth out the code transitions along vertical directions. The method further include computing a horizontal filter to be applied to the code image to smooth out the code transitions along horizontal directions, and computing a consistency filter to be applied to the code image to increase an accuracy of the code values and mark inconsistent pixels as invalid.

Abstract: In accordance with disclosed embodiments, there are provided systems, methods, and apparatuses for implementing maximum likelihood image binarization in a coded light range camera.