Abstract: In one embodiment, a method includes receiving, by an object reconstruction module, a first image and a second image. The first image includes a first region of an object and the second image comprises a second region of the object. The method also includes identifying, by the object reconstruction module, a transitional image. The transitional image includes the first region of the object and the second region of the object. The method further includes determining, by the object reconstruction module, that the first region of the object in the transitional image and the first region of the object in the first image are equivalent regions and generating, by the object reconstruction module, a reconstruction of the object using the first image and the transitional image. The reconstruction of the object includes the first region of the object and the second region of the object and excludes equivalent regions.

Abstract: Described is a method for segmenting measurement data from measurement of an object that has at least one material transition region. The measurement data are used to generate a digital object representation that has the material transition region and a multiplicity of spatially resolved image information items relating to the object. The method may include: determining measurement data that have at least one small structure having an extent which is less than a predefined extent; determining at least two homogeneous regions in the measurement data and/or in the digital object representation, wherein at least one homogeneous regions has a small structure; analysing a local similarity of the multiplicity of spatially resolved image information items; adapting an extent of each homogeneous region until at least one border region is arranged at an expected position of a material transition region; and segmenting the digital object representation based on the adapted homogeneous regions.

Abstract: A position detection apparatus comprises: a map information creation part that creates map information representing a position in a space including a floor surface on which at least one detection object may be disposed; a mask information creation part that creates mask information, by extracting a region of a predetermined height range within a height range from the floor surface when the detection object is disposed in the space from the map information; a specifying part that specifies partial optical image information, by removing a region corresponding to the mask information from the optical image information; and a detection part that specifies a positional relationship between the map information and the partial optical image information at a pixel level, and detects a position of the detection object in the map information based on the specified positional relationship.

Abstract: Techniques and systems are provided for high resolution time-of-flight (ToF) depth imaging. In some examples, an apparatus includes a projection system including one or more light-emitting devices, each light-emitting device being configured to illuminate at least one portion of an entire field-of-view (FOV) of the projection system. The entire FOV includes a plurality of FOV portions. The apparatus also includes a receiving system including a sensor configured to sequentially capture a plurality of images based on a plurality of illumination reflections corresponding to light emitted by the one or more light-emitting devices. Each image of the plurality of images corresponds to one of the plurality of FOV portions. An image resolution associated with each image corresponds to a full resolution of the sensor. The apparatus further includes a processor configured to generate, using the plurality of images, an increased resolution depth map associated with the entire FOV.

Abstract: A system includes sensors and a processor that tracks first and second objects in a space. Upon detecting that a tracked position of the first object is within a threshold distance of a tracked position of a second object, a top-view image of the first object is received from a first sensor. Based on this top-view image, a first descriptor is determined for the first object. The first descriptor is associated with an observable characteristic of the first object. The processor identifies the first object based at least in part upon the first descriptor.

Abstract: A map segmentation method and device, a motion estimation method, and a device terminal. Obtaining all map point data and constructing a corresponding graph based on these map points, where the graph includes each node formed by map points and corresponding edges; measuring and estimating to-be-estimated state variables corresponding to the node to obtain a corresponding measured and estimated value, where the to-be-estimated state variables include homogeneous coordinates of the node and a corresponding sensor pose upon node obtaining; calculating an inter-point correlation between any two adjacent nodes in the graph based on the measured and estimated value to determine whether the inter-point correlation is less than a preset correlation threshold; and when the inter-point correlation is less than the preset correlation threshold, removing an edge corresponding to the corresponding adjacent nodes, to separate the static points and the dynamic points and complete map segmentation.

Abstract: The present disclosure relates to a target tracking method, device, medium and apparatus, belongs to the technical field of computers, and can ensure the completeness of tracking. The target tracking method comprises performing object detection on all telephoto image frames captured by telephoto cameras in a multi-camera system, and constructing a detection point set based on object detection result for each frame of the telephoto image; selecting a target tracking point from each detection point set based on the starting tracking point; and connecting the selected target tracking points as a tracking sequence for the starting tracking point.

Abstract: A method for depth estimation performed by a depth estimation system of an autonomous agent includes determining a first pose of a sensor based on a first image captured by the sensor and a second image captured by the sensor. The method also includes determining a first depth of the first image and a second depth of the second image. The method further includes generating a warped depth image based on at least the first depth and the first pose. The method still further includes determining a second pose based on the warped depth image and the second depth image. The method also includes updating the first pose based on the second pose and updating a first warped image based on the updated first pose.

Abstract: A method for multi-camera monocular depth estimation using pose averaging is described. The method includes determining a multi-camera photometric loss associated with a multi-camera rig of an ego vehicle. The method also includes determining a multi-camera pose consistency constraint (PCC) loss associated with the multi-camera rig of the ego vehicle. The method further includes adjusting the multi-camera photometric loss according to the multi-camera PCC loss to form a multi-camera PCC photometric loss. The method also includes training a multi-camera depth estimation model and an ego-motion estimation model according to the multi-camera PCC photometric loss. The method further includes predicting a 360° point cloud of a scene surrounding the ego vehicle according to the trained multi-camera depth estimation model and the ego-motion estimation model.

Abstract: An information processing obtains a first image which is obtained by using a first camera to capture a three-dimensional space; obtains map information that is generated based on a second transformed image obtained by using second transformation information to geometrically transform a second image which has been captured by using a second camera to capture the three-dimensional space; generates a first transformed image by using first transformation information to geometrically transform the first image; and collates the map information and the first transformed image. The first transformation information and the second transformation information are set so that a geometric correspondence relationship between the three-dimensional space and the first transformed image and a geometric correspondence relationship between the three-dimensional space and the second transformed image will have a common geometric correspondence relationship.

Abstract: A computer-implemented method comprises obtaining first data comprising a first collection of coordinate data representing a position, or positions, of a first group of one or more objects detected in a first frame of a scene and obtaining second data comprising a second collection of coordinate data representing a position, or positions, of a second group of one or more objects detected in a second frame of the scene, wherein the second frame represents a different view of the scene than the first frame. The method further comprises determining whether any of the first group of objects correspond to any of the second group of objects in the scene based on the first collection of coordinate data and the second collection of coordinate data, wherein the first frame and the second frame are obtained from image data captured from a single camera position.

Abstract: The image processing device includes an imaging unit that images a subject and a distance map acquisition unit that acquires information regarding a distance distribution of the subject as map data. The distance map acquisition unit acquires map data with an image deviation amount or a defocused amount related to a captured image or distance map data in conformity with a TOF scheme or an imaging plane phase difference detection scheme of using a pupil division type image sensor. An image processing unit generates data of a texture image in which a low-frequency component of a captured image is inhibited and combines the data of the texture image and the map data acquired by the distance map acquisition unit to generate image data in which a distance distribution of a subject is expressed.

Abstract: An image processing device, an image processing system, an imaging device, an image processing method, and a recording medium storing program code. The image processing device includes a receiver configured to receive a first image and a second image, a memory configured to store a joining position at each one of a plurality of portions between the first image and the second image received by the receiver, and circuitry configured to evaluate, for each of the plurality of portions, validity of the joining position in a past stored in the memory, and generate a composite image based on the first image and the second image received by the receiver and the joining position in the past stored in the memory on a site where the validity meets a criterion. The method includes reading a past joining position at each one of a plurality of portions between a pair of images.

Abstract: A method of determining macrotexture of an object is presented which includes obtaining a plurality of stereo images from an object, generating a local coordinate system for each image, detecting one or more local keypoints each having a local coordinate, generating a global coordinate system based on a plurality of ground control points (GCPs) with apriori position knowledge of each of the plurality of GCPs, transforming the one or more local keypoints in each image to one or more global keypoints each having a global coordinate, generating a sparse point cloud based on the one or more global keypoints, reconstructing a 3D dense point cloud of the object based on neighboring pixels of each of the one or more local keypoints and calculating the global coordinates of each pixel of the 3D dense point cloud, and obtaining the macrotexture based on the reconstructed 3D dense point cloud of the object.

Abstract: A system and methods for a CODEC driving a real-time light field display for multi-dimensional video streaming, interactive gaming and other light field display applications is provided applying a layered scene decomposition strategy. Multi-dimensional scene data is divided into a plurality of data layers of increasing depths as the distance between a given layer and the plane of the display increases. Data layers are sampled using a plenoptic sampling scheme and rendered using hybrid rendering, such as perspective and oblique rendering, to encode light fields corresponding to each data layer. The resulting compressed, (layered) core representation of the multi-dimensional scene data is produced at predictable rates, reconstructed and merged at the light field display in real-time by applying view synthesis protocols, including edge adaptive interpolation, to reconstruct pixel arrays in stages (e.g. columns then rows) from reference elemental images.

Abstract: A method for creating a high-resolution image of an object from low-resolution images of the object is provided. Both the low-resolution images and the high-resolution image are composed of a pixel grid. An image recording device successively records low-resolution images, in which pitches of the grid points of the pixel grid are increased in one image dimension in comparison with the pitches of the grid points of the pixel grid in the high-resolution image to be created. A data processing system registers the low-resolution images with respect to one another to obtain registered images which are superimposed to obtain the high-resolution image. The grid points of the low-resolution images and the grid points of the high-resolution image have same dimensions and the data processing system uses image information obtained from different positions of the object relative to the grid points in the individual low-resolution images to create the high-resolution images.

Abstract: A system for controlling a physical system via segmentation of an image includes a controller. The controller may be configured to receive an image of n pixels from a first sensor, and an annotation of the image from a second sensor, form a coupling matrix, k class vectors each of length n, and a bias coefficient based on the image and the annotation, generate n pixel vectors each of length n based on the coupling matrix, class vectors, and bias coefficient create a single segmentation vector of length n from the pixel vectors wherein each entry in the segmentation vector identifies one of the k class vectors, output the single segmentation vector; and operate the physical system based on the single segmentation vector.

Abstract: An apparatus and method for executing a safety function is particularly applicable to monitoring a safety area of a technical installation. An imaging unit acquires an event that triggers the safety function within a defined working area. A controller carries out a safety-related reaction depending on the triggering event. A test unit is configured to verify the operability of the imaging unit and includes a processing unit and a projection unit. The projection unit projects a pattern with defined properties into the working area. The processing unit evaluates the image data acquired by the imaging unit to detect the projected pattern within the acquired image data. Further, the processing unit extracts the specific properties of the detected projected pattern, and compares the specific properties of the detected projected pattern with the defined properties.

Abstract: A character recognizing apparatus includes an acquiring unit, an identifying unit, and a character recognizing unit. The acquiring unit acquires a string image that is an image of a string generated in accordance with one of multiple string generation schemes. The identifying unit identifies a range specified for a result of character recognition in each of the multiple string generation schemes. The character recognizing unit performs first character recognition on the string image, and if a result of the first character recognition has a feature of a particular string generation scheme of the multiple string generation schemes, the character recognizing unit performs second character recognition on the string image within the range specified for a result of character recognition in the particular string generation scheme.

Abstract: Described is a method for instilling the haptic dimension of texture to virtual and holographic objects using mid-air ultrasonic technology. A set of features is extracted from imported images using their associated displacement maps. Textural qualities such as the micro and macro roughness are then computed and fed to a haptic mapping function together with information about the dynamic motion of the user's hands during holographic touch. Mid-air haptic textures are then synthesized and projected onto the user's bare hands. Further, mid-air haptic technology enables tactile exploration of virtual objects in digital environments. When a user's prior and current expectations and rendered tactile texture differ, user immersion can break. A study aims at mitigating this by integrating user expectations into the rendering algorithm of mid-air haptic textures and establishes a relationship between visual and mid-air haptic roughness.