Abstract: An intraocular pressure inspection device includes an intraocular pressure detection unit, a high-precision positioning system and a wide-area positioning system, wherein according to the position of the intraocular pressure detection unit, a set of high-precision coordinates output by the high-precision positioning system and a set of wide-area coordinates output by the wide-area positioning system are integrated in appropriate weights to obtain a set of more precise integrated coordinate. The above-mentioned intraocular pressure inspection device can prevent the intraocular pressure detection unit from failing to operate once it is not in the working area of the high-precision positioning system.

Abstract: The current disclosure describes techniques for forming a low resistance junction between a source/drain region and a nanowire channel region in a gate-all-around FET device. A semiconductor structure includes a substrate, multiple separate semiconductor nanowire strips vertically stacked over the substrate, a semiconductor epitaxy region adjacent to and laterally contacting each of the multiple separate semiconductor nanowire strips, a gate structure at least partially over the multiple separate semiconductor nanowire strips, and a dielectric structure laterally positioned between the semiconductor epitaxy region and the gate structure. The first dielectric structure has a hat-shaped profile.

Abstract: Various examples pertaining to emission and reception of patterned light waves for range sensing are described. An apparatus emits a light having a spatial pattern toward a scene. The apparatus performs range sensing of the scene using a hybrid of techniques based on a plurality of effects caused by the emitting of the light. The plurality of techniques include two or more active depth sensing techniques or a passive depth sensing technique and at least one active depth sensing technique.

Abstract: Various examples with respect to visual depth sensing with accurate and full-range depth fusion and sensing are described. A control circuit of an apparatus receives a plurality of sensor signals that are heterogeneous in type from a plurality of sensors. The control circuit generates first depth-related information of a scene and second depth-related information of the scene based on the plurality of sensor signals. The control circuit then fuses the first depth-related information and the second depth-related information to generate a fused depth map of the scene.

Abstract: Various examples with respect to infrared (IR) patter characteristics for stereo matching are described. A control circuit of an apparatus controls an IR projector to project a patterned IR light. In response, the control circuit receives first data of a left image of a scene from a first camera and second data of a right image of the scene from a second camera. The control circuit then performs stereo matching of the left image and the right image to generate a depth map of the scene. The patterned IR light satisfies one or more characteristic requirements.

Abstract: Various examples with respect to method and apparatus for active stereo vision are described. An apparatus may include an electromagnetic (EM) wave emitter, a first sensor and a second sensor. During operation, the EM wave emitter emits EM waves toward a scene, the first sensor captures a first image of the scene in an infrared (IR) spectrum, and the second sensor captures a second image of the scene in a light spectrum. The first image and second image, when processed, may enable active stereo vision.

Abstract: Various examples with respect to visual depth sensing with accurate and full-range depth fusion and sensing are described. A control circuit of an apparatus receives a plurality of sensor signals that are heterogeneous in type from a plurality of sensors. The control circuit generates first depth-related information of a scene and second depth-related information of the scene based on the plurality of sensor signals. The control circuit then fuses the first depth-related information and the second depth-related information to generate a fused depth map of the scene.

Abstract: Various examples with respect to infrared (IR) patter characteristics for stereo matching are described. A control circuit of an apparatus controls an IR projector to project a patterned IR light. In response, the control circuit receives first data of a left image of a scene from a first camera and second data of a right image of the scene from a second camera. The control circuit then performs stereo matching of the left image and the right image to generate a depth map of the scene. The patterned IR light satisfies one or more characteristic requirements.

Abstract: Various examples with respect to method and apparatus for active stereo vision are described. An apparatus may include an electromagnetic (EM) wave emitter, a first sensor and a second sensor. During operation, the EM wave emitter emits EM waves toward a scene, the first sensor captures a first image of the scene in an infrared (IR) spectrum, and the second sensor captures a second image of the scene in a light spectrum. The first image and second image, when processed, may enable active stereo vision.

Abstract: A method for generating a target perspective model referenced for depth map generation includes at least following steps: receiving a first input image; utilizing a region-based analysis unit for analyzing a plurality of regions in the first input image to extract image characteristics of the regions; and determining the target perspective model according to at least the image characteristics. Another method for generating a target perspective model referenced for depth map generation includes: receiving a first input image; determining a first perspective model in response to the first input image; and utilizing a perspective model generation unit for generating the target perspective model by a weighted sum of the first perspective model and at least one second perspective model.

Abstract: An example process to enhance a two-dimensional (2D) image may include generating a depth map for the 2D image based on edges detected from the 2D image, wherein the depth map can be used to convert the 2D image to a 3D image. The process may further include enhancing the 2D image using the depth map.

Abstract: An image processing method comprising: (a) receiving at least one input image; (b) acquiring depth map from the at least one input image; and (c) performing a defocus operation according to the depth map upon one of the input images, to generate a processed image.

Abstract: A 3D displaying method, comprising: acquiring distance information map from at least one image; receiving control information from a user input device; modifying the distance information map according to the control information to generate modified distance information map; generating an interactive 3D image according to the modified distance information map; and displaying the interactive 3D image.

Abstract: A stereoscopic display apparatus is provided. The stereoscopic display apparatus includes a liquid crystal panel, a backlight, a controller and an active polarizer disposed adjacent to the liquid crystal panel. The liquid crystal panel alternately displays a left image and a right image to passive polarized glasses according to a synchronization signal. The backlight supplies light to the liquid crystal panel. The controller provides the left image, the right image and the synchronization signal according to a video input signal. The active polarizer polarizes the light from the backlight in response to the synchronization signal to form two viewing zones, such that the left image and the right image are observed by the passive polarized glasses via the corresponding zones, respectively.

Abstract: In accordance with at least some embodiments of the present disclosure, a processor for performing stereo matching of a first image and a second image is described. The processor may include a first pipeline stage configured to generate data costs associated with a first tile selected from the first image, wherein the data costs is generated based on pixels in the first tile and corresponding pixels in the second image. The processor may include a second pipeline stage configured to generate disparity values associated with the first tile and an outbound message from the first tile to one of neighboring tiles in the first image, wherein the disparity values and the outbound message are generated based on the data costs and inbound messages from the neighboring tiles to the first tile.

Abstract: A system and method of correcting a depth map for 3D image is disclosed. A spatial spectral transform unit extracts pixels of object boundaries according to an input image, wherein the spatial spectral transform unit adopts Hilbert-Huang transform (HHT). A correction unit corrects an input depth map corresponding to the input image according to the pixels of object boundaries, thereby resulting in an output depth map.

Abstract: A method of revising depth of a three-dimensional (3D) image is disclosed. The method comprises the following steps: firstly, at least one initial depth map associated with one image of the 3D image pair based on stereo matching technique is received, wherein the one image comprises a plurality of pixels, and the initial depth map carries an initial depth value of each pixel. Then, the inconsistence among the pixels of the one image of the 3D image pair is detected to estimate a reliable map. Finally, the initial depth value is interpolated according to the reliable map and the proximate pixels, so as to generate a revised depth map by revising the initial depth value.

Abstract: In accordance with at least some embodiments of the present disclosure, a process for generating a depth map for converting a two-dimensional (2D) image to a three-dimensional (3D) image is described. The process may include generating a depth gradient map from the 2D image, wherein the depth gradient map is configured to associate one or more edge counts with one or more depth values, extracting an image component from the 2D image, wherein the image component is associated with a color component in a color space, determining a set of gains to adjust the depth gradient map based on the image component, and generating the depth map by performing depth fusion based on the depth gradient map and the set of gains.

Abstract: An exemplary depth control method includes following steps: receiving input images corresponding to different views; generating at least one depth-related information map according to the input images; estimating a confidence level by measuring quality of the depth-related information map; and adjusting the depth-related information map according to the confidence level. In addition, an exemplary depth control apparatus includes a depth-related information map generation circuit, a quality measurement circuit and an adjustment circuit. The depth-related information map generation circuit receives input images corresponding to different views, and generates at least one depth-related information map according to the input images. The quality measurement circuit estimates a confidence level by measuring quality of the depth-related information map. The adjustment circuit adjusts the depth-related information map according to the confidence level.

Abstract: An embodiment of the invention provides a disparity search method for searching for a matching pixel block from a second image of a multi-view video. The matching pixel block corresponds to a given pixel block of a first image of the multi-view video; the first image and the second image are spatially adjacent to each other. First, a set of reference pixel blocks is selected from a set of reference images of the multi-view video to provide a set of reference disparity vectors. Then, a set of disparity vector predictors is prepared based on the set of reference disparity vectors, wherein the given pixel block's position and the set of disparity vector predictors define a set of candidate pixel blocks in the second image. Next, the set of candidate pixel blocks in the second image is searched for the matching pixel block.