Abstract: An SN ratio of light to be received is improved. A polarizing filter (150) that is arranged in a light path extending from an object (11) to a light receiving unit (154) of a ToF sensor (153) and allows transmission of light polarized in a direction vertical to a direction of scanning is provided.

Abstract: A method for automated calibration is provided. The method may include obtaining a plurality of interest points based on prior information regarding a device and image data of the device captured by a visual sensor. The method may include identifying at least a portion of the plurality of interest points from the image data of the device. The method may also include determining a transformation relationship between a first coordinate system and a second coordinate system based on information of at least a portion of the identified interest points in the first coordinate system and in the second coordinate system that is applied to the visual sensor or the image data of the device.

Abstract: A method for depth sensing from an image of a projected pattern is performed at an electronic device with one or more processors and memory. The method includes receiving an image of a projection of an illumination pattern; for a portion of the image, selecting a candidate image of a plurality of candidate images by comparing the portion of the image with a plurality of candidate images; and determining a depth for the portion of the image based on depth information associated with the selected candidate image. Related electronic devices and computer readable storage medium are also disclosed.

Abstract: A depth estimation method and apparatus are provided. The depth estimation method includes obtaining an image from an image sensor comprising upper pixels, each comprising N sub-pixels, obtaining N sub-images respectively corresponding to the N sub-pixels from the image, obtaining a viewpoint difference between the N sub-images using a first neural network, and obtaining a depth map of the image based on the viewpoint difference using a second neural network.

Abstract: A survey tool for determining position and orientation (P&O) thereof relative to a construction site is provided herein. The survey tool may include: a moveable platform wherein the moveable platform is configured to rotate at least one two-axis electro-optic deflection unit mounted on the moveable platform; at least one light source coupled to the two-axis electro-optic deflection unit configured to project a light beam, wherein steering of the light beam is carried out by operating at least one of: the two-axis electro-optic deflection unit, and the moveable platform, and wherein the light beam forms a projection onto surfaces within the construction site; at least one sensor configured to record at least one of: a steering angle and, a distance between the survey tool and said point; and at least one computer processor configured to determine the P&O of the survey tool relative to the construction site.

Abstract: The purpose of the present invention is to provide an imaging device whereby enhanced sensing precision and reduced computational load can both be achieved at the same time even when a plurality of objects as sensing subjects are present. In order to achieve this purpose, the present invention has: a first object detection processing unit having a plurality of imaging units, the first object detection processing unit performing first object detection processing for sensing, by stereo processing, a distance for each of a plurality of image elements in partial region of interest in an image acquired by the imaging units, then extracting a group of the image elements on the basis of the sensed distances and detecting an object; and a second object detection processing unit for performing second object detection processing for detecting the distance of the object by stereo processing for a partial region of another region of interest in the image.

Abstract: A distance measurement device includes an imaging unit which captures a subject image formed by an imaging optical system forming the subject image indicating a subject, an emission unit which emits directional light as light having directivity along an optical axis direction of the imaging optical system, a light receiving unit which receives reflected light of directional light from the subject, a derivation unit which derives a distance to the subject based on a timing at which directional light is emitted by the emission unit and a timing at which reflected light is received by the light receiving unit, and a control unit which performs control such that at least a part of an imaging period by the imaging unit overlaps at least a part of a distance measurement period by the emission unit, the light receiving unit, and the derivation unit.

Abstract: A height measurement device includes: a lens system; a lens controller to output a drive signal to the lens system; a continuous illuminator to continuously illuminate a workpiece; an image detector to detect an image of the workpiece; an image calculation unit to calculate an EDOF image on a basis of a detected image; a focal depth adjustment unit to cause an extended focal depth of the EDOF image to be increased or decreased by increasing or decreasing an amplitude of the drive signal; a focus determination unit to determine a focus state of a portion of interest of the workpiece included in the EDOF image; and a height measurement unit to measure an upper limit or a lower limit of the extended focal depth, the upper limit or the lower limit being based on a timing at which the focus state of the portion of interest has changed.

Abstract: A video acoustical method determines an impact point of a thrown body on a landing area, in particular for athletics throws disciplines, the body describing a trajectory in the air from a take-off area towards the landing area, the impact point being defined by the body hitting on the landing area. The method includes acquiring video exposures of the body impact on the landing area to a frame rate, each exposure showing one position of the body; calculating the body trajectory during at least the body impact on the landing area with the video exposures analysis; detecting an acoustical impact time due to the body hitting on the landing area; and determining the body impact point on the calculated trajectory with the detected acoustical impact time. A video acoustical system can determine an impact point of a thrown body on a landing area.

Abstract: An image sensor according to an embodiment of the present invention includes: a pixel array in which a plurality of pixels are arrayed in a grid shape, and which converts reflection light signals reflected from an object into electrical signals; an image processor which converts the electrical signals to generate subframes, and extracts pieces of second depth information having a higher resolution than pieces of first depth information extracted from a plurality of the subframes; and a memory for storing the pieces of first depth information, wherein the reflection light signals are input to the pixel array through mutually different optical paths shifted in sub-pixel units of the pixel array, and the memory stores a plurality of the pieces of first depth information that correspond to the mutually different optical paths.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned communication. One of the methods includes: receiving an RF signal at a signal processing system for training a machine-learning network; providing the RF signal through the machine-learning network; producing an output from the machine-learning network; measuring a distance metric between the signal processing model output and a reference model output; determining modifications to the machine-learning network to reduce the distance metric between the output and the reference model output; and in response to reducing the distance metric to a value that is less than or equal to a threshold value, determining a score of the trained machine-learning network using one or more other RF signals and one or more other corresponding reference model outputs, the score indicating an a performance metric of the trained machine-learning network to perform the desired RF function.

Abstract: Embodiments provide for a method of determining a geospatial position of a point of interest and a portable positioning device. In one embodiment, the method includes collecting data from a receiving unit and data from at least one of an imaging device and an IMU of the positioning device for each one of a plurality of positions of the positioning device. The collected data is then transmitted to a data fusing processor for determining orientations and positions of the positioning device for the plurality of positions in a global coordinate system. Further, the method includes obtaining a pointing input including a sighting direction towards the point of interest from the positioning device being positioned at at least one reference position. The pointing input is transmitted to the data fusing processor for identifying the point of interest and for determining the geospatial position of the point of interest in the global coordinate system.

Abstract: A system uses a fleet of AVs to assess visibility of target objects. Each AV has a camera for capturing images of target objects. AVs provide the captured images, or visibility data derived from the captured images, to a remote system, which aggregates visibility data describing images captured across the fleet of AVs. The AVs also provide condition data describing conditions under which the images were captured, and the remote system aggregates the condition data. The remote system processes the aggregated visibility data and condition data to determine conditions under which a target object does not meet a visibility threshold.

Abstract: The present disclosure relates to a host vehicle and control method thereof, according to one aspect of the present disclosure, the purpose is to enable quick and accurate recognition of cut-in vehicles that change lanes from adjacent lanes to travel lanes. Disclosed are a control method of a host vehicle, the method including: obtaining a front image by photographing the front of the host vehicle; identifying left and right lines of a travel lane in which the host vehicle is traveling from the front image; determining that a vehicle cutting-in from an adjacent lane to the travel lane exists when the lengths of the left line and the right line of the travel lane are different from each other in the front image.

Abstract: A system of generating a three-dimensional (3D) scan of an environment includes multiple 3D scanners including a first 3D scanner at respective first and second positions. The system further includes a controller coupled to the 3D scanners via a common communications network. The first scanner and second scanner transmit a subset of data to the controller while acquiring a set of 3D coordinates. The controller registers the subsets of data to each other while the sets of 3D coordinates is being acquired.

Abstract: Robot localization or mapping can be provided without requiring the expense or complexity of an “at-a-distance” sensor, such as a camera, a LIDAR sensor, or the like. Landmark features can be created or matched using motion sensor data, such as odometry or gyro data or the like, and adjacency sensor data. Despite the relative ambiguity of adjacency-sensor derived landmark features, a particle filter approach can be configured to use such information, instead of requiring “at-a-distance” information from a constant stream of visual images from a camera, such as for robot localization or mapping. Landmark sequence constraints or a Wi-Fi signal strength map can be used together with the particle filter approach.

Abstract: The present invention relates to a method for size estimation by image recognition of a specific target using a given scale. First, a reference objected is recognized in an image and the corresponding scale is established. Then the specific target is searched and the size of the specific target is estimated according to the acquired scale.

Abstract: A method for fusing a first occupancy map and a second occupancy map comprises: determining at least one fusion parameter representing a potential dissimilarity between the first occupancy map and the second occupancy map and determining a fused occupancy map representing free and occupied space around the vehicle. The fused occupancy map is determined based on the first occupancy map, the second occupancy map, and a fusion rule. The fusion rule is configured to control the influence of the first occupancy map and/or the second occupancy map on the fused occupancy map based on the at least one fusion parameter.

Abstract: Methods and systems for determining a displacement of a peripheral device are provided. In one example, a peripheral device comprises: an image sensor, and a hardware processor configured to: control the image sensor to capture a first image of a surface when the peripheral device is at a first location on the surface, the first image comprising a feature of the first location of the surface; execute a trained machine learning model using data derived from the first image to estimate a displacement of the feature between the first image and a reference image captured at a second location of the surface; and determine a displacement of the peripheral device based on the estimated displacement of the feature.

Abstract: Embodiments of the present disclosure relate to a three-dimensional reconstruction method and apparatus for a material pile, an electronic device, and a computer-readable medium. The method may include: acquiring, in response to an instruction for controlling an excavator body of an excavator to rotate to transport materials being detected, a sequence of depth images of an excavated material pile collected by a binocular camera provided on a side of the excavator; and performing three-dimensional reconstruction based on the sequence of depth images of the material pile, to generate a three-dimensional model of the material pile.

Abstract: To estimate the top surface of a measurement target on the basis of a data point group that corresponds to the top surface of a measurement target and is obtained using a laser scanner. This top surface estimation method for hoisting loads and by acquiring, using the laser scanner, data point groups in a hoisting load region which includes a hoisting load and an object from above the hoisting load and the object, dividing the hoisting load region into layers which constitute a plurality of groups which have a prescribed thickness in the vertical direction, and allocating the acquired data point groups to the plurality of layer groups, and estimating the top surfaces of the hoisting load and the object in each layer group on the basis of the data point groups allocated to the plurality of layer groups.

Abstract: An image processing apparatus, an image processing method, a program, and a recording medium storing the program capable of extracting, from an input first image group, an image similar to an image extracted from a reference image group are provided. A first image group including a plurality of images of a user is transmitted to an order reception server. A second image group similar to the first image group is searched from a plurality of reference image groups stored in the order reception server. An image similar to an image previously extracted from the second image group is extracted from the first image group. An album is generated by arranging the image extracted from the first image group in a layout similar to a layout of an album generated from the second image group.

Abstract: A reduction in quality of a virtual viewpoint image is suppressed. An image processing apparatus specifies an image in which a specific position in a target object is not occluded by another object from among a plurality of images obtained by the plurality of imaging apparatuses based on a pixel value of the plurality of images; determines, based on the specified image, a value of a pixel corresponding to the specific position in the virtual viewpoint image to be generated based on the plurality of images; and generates the virtual viewpoint image including the target object based on the determined value of the pixel.

Abstract: A server apparatus includes a communication interface and a controller configured to transmit and receive information via the communication interface, wherein the controller is configured to transmit an instruction for controlling light emission by a plurality of floor coverings, each floor covering including a light emitting element, to the plurality of floor coverings based on positional information for a first point where a pedestrian is located in an area where the plurality of floor coverings are disposed and positional information for a second point different from the first point in the area.

Abstract: A calibration device fora 3D (three dimensional) camera and a robotic arm includes three plates with fixed relative positions and non-parallel separation disposed on a mount. Three spatial planes extending from the three plates intersect at a positioning point for external parameter correction. A calibration method for coordinates of a 3D (three dimensional) camera and a robotic arm using the calibration device is also specified in detail.

Abstract: An apparatus acquires a plurality of candidate correct answer images for generating a correct answer image that is used for image quality evaluation, and detects a candidate correct answer image to be excluded from the acquired plurality of candidate correct answer images, based on differences between the acquired plurality of candidate correct answer images.

Abstract: There is provided with an image processing apparatus. A detection unit detects an object from a captured image. A generation unit generates a map representing a correspondence between objects detected in a plurality of captured images. A determination unit matches the objects detected in the plurality of captured images based on the generated map.

Abstract: A calibration method for a robotic arm system is provided. The method includes: capturing an image of a calibration object fixed to a front end of the robotic arm by a visual device, wherein a pedestal of the robotic arm has a pedestal coordinate system, and the front end of the robotic arm has a first relative relationship with the pedestal, the front end of the robotic arm has a second relative relationship with the calibration object; receiving the image and obtaining three-dimensional feature data of the calibration object according to the image by a computing device; and computing a third relative relationship between the visual device and the pedestal according to the three-dimensional feature data, the first relative relationship, and the second relative relationship to calibrate a position error between a physical location of the calibration object and a predictive positioning-location generated by the visual device.

Abstract: The measurement system 100 includes: a measurement apparatus 20 that measures vibrations of an object 40; an imaging apparatus 30 that is located so as to capture an image of the measurement apparatus 20; and a correction processing apparatus 10. the correction processing apparatus 10 includes: a displacement calculation unit 11 that calculates a displacement of the measurement apparatus 20 based on time-series images of the measurement apparatus 20 output from the imaging apparatus 30; a movement amount calculation unit 12 that calculates an amount of movement of the measurement apparatus 20 relative to the imaging apparatus 30, based on the displacement; and a correction processing unit 13 that corrects vibrations of the object measured by the measurement apparatus 20, using the calculated amount of movement of the measurement apparatus 20.

Abstract: Provided are a panoramic photographing method and device, a camera and a mobile terminal, the method includes: when panoramic photographing is performed, firstly, a ranging device acquires the depth information of the object to be photographed, that is, the distance between the object to be photographed and the photographing device, and then the offset corresponding to the current distance is acquired according to a preset mapping relationship, and the original imaging of the object to be photographed is subsequently shifted in the panoramic image to form a corrected panoramic image.

Abstract: A method for autonomously maneuvering a tow vehicle towards a trailer positioned behind the tow vehicle is provided. The method includes receiving one or more images from one or more cameras positioned on a back portion of the tow vehicle. The method also includes identifying a trailer representation within the one or more images. The trailer representation being indicative of the trailer positioned behind the tow vehicle. The method also includes setting a vertical center of the trailer representation as a target. The method also includes determining a first steering wheel angle to turn the tow vehicle such that the vehicle autonomously maneuvers in a direction towards the target. The method also includes transmitting instructions to a drive system causing the tow vehicle to maneuver based on the first steering wheel angle.

Abstract: Various embodiments disclosed herein include techniques for determining autofocus for a camera on a mobile device. In some instances, depth imaging is used to assist in determining a focus position for the camera through an autofocus process. For example, a determination of depth may be used to determine a focus position for the camera. In another example, the determination of depth may be used to assist another autofocus process.

Abstract: A position detection system detects a position of an object by using a plurality of frames, each of the plurality of frames being divided into a plurality of subframes. The position detection system includes: a projector configured to project a plurality of gray code patterns having different gray code values in an order of ascending and then descending or descending and then ascending of the different gray code values, each of the plurality of gray code patterns corresponding to a corresponding one of the plurality of subframes, each of the different gray code values being a power of two; an imaging device configured to generate a captured image by, for each of the plurality of subframes, imaging the object on which the plurality of gray code patterns are projected; a controller configured to estimate the position of the object based on the captured image.

Abstract: A safe optoelectronic sensor is provided for securing a monitored zone comprising at least one machine, wherein the sensor has at least one light receiver for generating a received signal from received light from the monitored zone and a control and evaluation unit that is configured to determine distances from objects in the monitored zone from the received signal, and to treat gaps, i.e. safety relevant part regions of the monitored zone in which no reliable distance can be determined, as an object at a predefined distance. The predefined distance here corresponds to a height for securing against reach over.

Abstract: A method for wirelessly coupling respective transducers of an automated motion platform and a sub-surface sensor node through a skin of a limited-access structure for the purpose of wireless power and data transfer. Coordinates of an as-designed position of the transducer of the sensor node in a local coordinate system of the limited-access structure are retrieved from a non-transitory tangible computer-readable storage medium. Then coordinates of a target position on an external surface of the skin of the limited-access structure are estimated. The target position is calculated to be aligned with the as-designed position of the transducer of the sensor node. The motion platform is moved under computer control so that the transducer onboard the motion platform moves toward the target position. Movement ceases when the transducer onboard the motion platform is at the target position. Then wave energy is transferred between the aligned transducers.

Abstract: Techniques are described for automated operations to analyze visual data combined from multiple images captured in a room to determine the room shape, such as by iteratively refining alignment of the multiple images' visual data into a common coordinate system until alignment differences satisfy one or more defined criteria, and for subsequently using the determined room shape information in further automated manners. The images may be panorama images in an equirectangular or other spherical format, and determined room shapes for one or more rooms of a building may be fully closed three-dimensional shapes and used to improve navigation of the building (e.g., as part of a generated building floor plan)—the automated room shape determination may be further performed without having or using information from any distance-measuring devices about distances from an image's acquisition location to walls or other objects in the surrounding room.

Abstract: A surveying instrument comprises a base; an alidade rotatable about a first axis relative to the base; and an optical measuring instrument having a measuring axis rotatable about a second axis relative to the alidade. A beam path can be provided for a light beam using components including a light source, lenses, mirrors, beam splitters, and a position-sensitive detector. The surveying can be calibrated by performing plural measurements at different orientations of the alidade relative to the base and different orientations of the measuring instrument relative to the alidade using the above components.

Abstract: Embodiments of the disclosure relate generally to flicker reduction in a multi-imager environment. Embodiments include methods, computer program products, and apparatuses configured for producing a near-field illumination using a near-field illuminator, the near-field illumination produced at a defined pulse train. A near-field image sensor may be exposed near the start of a near-field illumination pulse, and a far-field image sensor may be exposed between pulses of the near-field illumination. Some embodiments, additionally or alternatively, are configured for detecting an illuminator switch event, deactivating the near-field illuminator source, and producing, using a far-field illuminator source, a far-field illumination. Upon switching the illuminator source, some such embodiments are configured for exposing a far-field illuminator near the start of the far-field illumination pulse, and exposing a near-field image sensor near the start of the next available far-field illumination pulse.

Abstract: Techniques are described for using computing devices to perform automated operations to generate mapping information using inter-connected images of a defined area, and for using the generated mapping information in further automated manners. In at least some situations, the defined area includes an interior of a multi-room building, and the generated information includes a floor map of the building, such as from an automated analysis of multiple panorama images or other images acquired at various viewing locations within the building—in at least some such situations, the generating is further performed without having detailed information about distances from the images' viewing locations to walls or other objects in the surrounding building. The generated floor map and other mapping-related information may be used in various manners, including for controlling navigation of devices (e.g., autonomous vehicles), for display on one or more client devices in corresponding graphical user interfaces, etc.

Abstract: A system for generation of training dataset is provided. The system controls a depth sensor to capture, from a first viewpoint, a first image a first depth value associated with the first object. The system receives tracking information from a handheld device associated with the depth sensor, based on a movement of the handheld device and the depth sensor in a 3D space. The system generates graphic information corresponding to the first object based on the received tracking information. The graphic information includes the first object from a second viewpoint. The system calculates a second depth value associated with the first object, based on the graphic information. The system generates, for a neural network model, a training dataset which includes a first combination of the first image and the first depth value, and a second combination of second images corresponding to the graphic information and the second depth value.

Abstract: A method for automated calibration is provided. The method may include obtaining a plurality of interest points based on prior information regarding a device and image data of the device captured by a visual sensor. The method may include identifying at least a portion of the plurality of interest points from the image data of the device. The method may also include determining a transformation relationship between a first coordinate system and a second coordinate system based on information of at least a portion of the identified interest points in the first coordinate system and in the second coordinate system that is applied to the visual sensor or the image data of the device.

Abstract: In a distance measuring device that measures a distance to an object using a round-trip time of light, a solid-state image sensor includes a plurality of pixel groups capable of being exposed independently, and causes each of the plurality of pixel groups to receive, at a different exposure time, reflected light from the object that is originally pulsed radiation light from a light emitter. A light emission and exposure controller cyclically and intermittently exposes each of the plurality of pixel groups of the solid-state image sensor at the different exposure time to obtain pixel signals of types corresponding to a time difference between the reflected light and the radiation light, and a signal processor obtains information about the distance to the object according to pixel signals of adjacent pixels exposed at different exposure times for each of the plurality of pixel groups.

Abstract: An image processing apparatus 10 includes an interface 12 configured to acquire a stereo image that includes a standard image and a reference image captured from different viewpoints and a processor 13 configured to perform low-rank approximation by singular value decomposition on the standard image and the reference image, and calculate a parallax by performing stereo matching processing between the standard image and the reference image that are subjected to the low-rank approximation by the singular value decomposition.

Abstract: Embodiments of the present specification provide systems and methods to provide a 3D experience in a 2D game, while using the same underlying gaming engine. A 2D game space representing an axonometric projection is overlaid with 3D visuals, in a way that the original 2D simulation can still be used to run the game. In embodiments, a set of custom tools are used to map the 2D ground plane to a 3D ground plane. The 2D objects are then mapped into 3D objects. The 3D game environment corresponding to the original 2D game layout is created at backend by one or more individuals, using custom graphic tools. Dynamic player remap in 3D is generated in real time while the player engages with the 2D game. Therefore, while a player is playing the 2D game, a dynamic equivalent of the game in 3D is rendered.

Abstract: The present disclosure provides a method for generating an object detection box, comprises: obtaining a set of point-cloud data frames collected by a radar device within a set period; obtaining, from the set, a first point-cloud data frame corresponding to a first time when an unmanned vehicle is closest to a target object, and obtaining first detection box information corresponding to the target object in the first point-cloud data frame that is obtained through an automatic detection algorithm; determining whether the first detection box information is valid detection box information with respect to a second cloud-point data frame in the set that corresponds to a second time prior to the first time; and determining whether the first detection box information is to be used as final detection box information of the target object in the second point-cloud data frame according to the result of the determination.

Abstract: Motion of actors within a scene may be detected based on imaging data, using machine learning tools operating on cameras that captured the imaging data. The machine learning tools process images to perform a number of tasks, including detecting heads of actors, and sets of pixels corresponding to the actors, before constructing line segments from the heads of the actors to floor surfaces on which the actors stand or walk. The line segments are aligned along lines extending from locations of heads within an image to a vanishing point of a camera that captured the image. Trajectories of actors and visual data are transferred from the cameras to a central server, which links trajectories captured by multiple cameras and locates detected actors throughout the scene, even when the actors are not detected within a field of view of at least one camera.

Abstract: In accordance with some embodiments, systems, methods and media for directly recovering planar surfaces in a scene using structured light are provided. In some embodiments, a system comprises: a light source; an image sensor; a processor programmed to: cause the light source to emit a pattern comprising a pattern feature with two line segments that intersect on an epipolar line; cause the image sensor to capture an image including the pattern; identify an image feature in the image, the image feature comprising two intersecting line segments that intersect at a point in the image that corresponds to the first epipolar line; estimate a plane hypothesis associated with the pattern feature based on properties of the pattern feature and properties of the image feature, the plane hypothesis associated with a set of parameters characterizing a plane; and identify a planar surface in the scene based on the plane hypothesis.

Abstract: A system and a method for processing images are provided. The method may include one or more of the following operations. An image including a plurality of channels and a plurality of pixels may be obtained, each pixel having a pixel value corresponding to one of the plurality of channels. One of the plurality of pixels may be selected as a pixel of interest, and the corresponding channel of the pixel value of the pixel of interest may be designated as a target channel. A plurality of pixels proximate to the pixel of interest may include at least two first reference pixels. For each first reference pixel, a pseudo pixel value for the target channel of the first reference pixel may be determined. Whether the image is a deteriorated image may be determined at least based on the pixel value of the pixel of interest and the determined pseudo pixel values.

Abstract: An example method for performing depth measurements with an image sensor comprises, for at least a first pixel, performing one or more continuous-wave phase measurements for the first pixel and performing a coded-modulation measurement for the first pixel. The method further comprises determining a mask value for the first pixel, based on the coded-modulation measurement, and applying the mask value to a distance value calculated from the one or more continuous-wave phase measurements, to obtain a masked distance value for the first pixel that has no ambiguity due to phase wrapping.

Abstract: An illustrative computing system is configured to perform volumetric reconstruction based on a confidence field. In one implementation, the computing system accesses color and depth data captured from a plurality of different vantage points for a surface point on a surface of an object. Based on the color and depth data captured from the plurality of different vantage points, the computing system determines a confidence field value associated with the surface point. Based on the confidence field value associated with the surface point, the computing system generates reconstructed color and depth data for a volumetric reconstruction of the surface of the object. Corresponding methods and systems are also disclosed.