Abstract: Embodiments of the present disclosure relate to a self-driving system having an RFID reader and a built-in printer. In one embodiment, a self-driving system includes a mobile base having one or more motorized wheels, the mobile base having a first end and a second end opposing the first end, a console coupled in an upright position to the first end of the mobile base, and a tag reader integrated with the console, the tag reader having a sensor surface facing upwardly.

Abstract: Embodiments of the present disclosure relate to a self-driving system having an RFID reader and a built-in printer. In one embodiment, a self-driving system includes a mobile base having one or more motorized wheels, the mobile base having a first end and a second end opposing the first end, a console coupled in an upright position to the first end of the mobile base, and a tag reader integrated with the console, the tag reader having a sensor surface facing upwardly.

Abstract: Embodiments of the present disclosure relate to a self-driving system having an RFID reader and a built-in printer. In one embodiment, a self-driving system includes a mobile base having one or more motorized wheels, the mobile base having a first end and a second end opposing the first end, a console coupled in an upright position to the first end of the mobile base, and a tag reader integrated with the console, the tag reader having a sensor surface facing upwardly.

Abstract: Described are methods and systems for real-time remote avatar creation and animation control. A sensor device captures images of non-rigid objects in a scene. A server coupled to the sensor device generates an initial 3D model for each of the non-rigid objects in the scene using the images. The server detects landmark points on the non-rigid objects using the initial 3D model. The server generates a control point animation map for the 3D model using the detected points. The server applies the animation map to the 3D model to generate a mapped 3D model. A viewer coupled to the server receives (i) the mapped 3D model and (ii) tracking information associated with the objects, including a model pose and deformation of the landmark points. The viewer modifies the mapped 3D model using the tracking information, and renders a video stream on the viewer using the modified 3D model.

Abstract: Described herein are methods and systems for three-dimensional (3D) object capture and object reconstruction using edge cloud computing resources. A sensor coupled to a mobile device captures (i) depth maps of a physical object, the depth maps including pose information, and (ii) color images of the object. An edge cloud device coupled to the mobile device via a 5G connection receives the depth maps and the color images. The edge cloud device generates a new 3D model of the object based on the depth maps and color images, when a 3D model of the object has not been generated. The edge cloud device updates an existing 3D model of the object based on the depth maps and color images, when a 3D model of the object has previously been generated. The edge cloud device transmits the new 3D model or the updated 3D model to the mobile device.

Abstract: Described herein are methods and systems for remote visualization of three-dimensional (3D) animation. A sensor of a mobile device captures scans of non-rigid objects in a scene, each scan comprising a depth map and a color image. A server receives a first set of scans from the mobile device and reconstructs an initial model of the non-rigid objects using the first set of scans. The server receives a second set of scans. For each scan in the second set of one or more scans, the server determines an initial alignment between the depth map and the initial model. The server converts the depth map into a coordinate system of the initial model, and determines a displacement between the depth map and the initial model. The server deforms the initial model to the depth map using the displacement, and applies a texture to at least a portion of the deformed model.

Abstract: A method and device for realizing a verification code are provided. In some embodiments, a character verification code is obtained and displayed when it is determined to perform identity verification. The character verification code has an incorrect character based on a priori knowledge. The user is prompted to input a correct character corresponding to the incorrect character in the character verification code. Verification information is received. It is determined that the verification is successful when the verification information corresponds to the correct character of the prior knowledge; otherwise, the verification failed.

Abstract: An information processing method, a terminal and a computer storage medium are disclosed. Here, the information processing method includes that: information of a first image is pre-acquired, and a first encryption key is generated and stored; information of a second image is acquired; a first image characteristic and second image characteristic of the information of the second image are extracted, wherein the first image characteristic represents background information of the first image, and the second image characteristic represents foreground information of the first image; a third image characteristic is obtained on the basis of the first image characteristic and the second image characteristic, and the third image characteristic is determined as a second encryption key; and similarity matching is performed on the second encryption key and the pre-stored first encryption key to generate a matching result, and a second image is authenticated according to the matching result.

Abstract: An information handling system operating a learning dynamic gamma-correction optimization system may execute a method including identifying a combination of red, green, and blue subpixel component values for a plurality of pixels, and determining optimal red, green, and blue subpixel component values for the plurality of pixels by running a gamma correction algorithm using a gamma correction factor associated with a maximum gradient energy between the plurality of pixels.

Abstract: Described herein are methods and systems for keyframe-based object scanning and tracking. A sensor device captures images of objects in a scene. For each image, a computing device labels each of at least a plurality of pixels in the image, tracks at least one region of the labeled image to determine an estimate of a current pose of at least one object, validates the estimate of the current pose of the at least one object, selects the labeled image as a keyframe based upon validation of the estimate of the current pose, and updates a volumetric model comprising the at least one object using the keyframe. The computing device generates a final 3D model of the at least one object based upon the updated volumetric model.

Abstract: The present disclosure discloses a CAPTCHA image generation method and apparatus, and a server, relating to the field of computer technologies. According to the present disclosure, first noise points are generated on a CAPTCHA code in some regions of an initial image and second noise points are generated on a background of the image in another region, so that a machine cannot filter out the noise points in a CAPTCHA image by means of some simple algorithms, increasing difficulty in recognizing the CAPTCHA code by the machine, reducing a risk that the CAPTCHA code is cracked by the machine, and having a strong crack-proof capability.

Abstract: Described are methods, systems, and apparatuses for 3D vision processing using an IP block. A vision processing module comprises an integrated circuit that performs one or more 3D vision processing algorithms and a plurality of controllers that couple the integrated circuit to each of: a sensor device, a processor, a memory module, and a network interface. The vision processing module receives image data from the sensor device, the image data corresponding to one or more images captured by the sensor device. The vision processing module executes one or more of the 3D vision processing algorithms using at least a portion of the image data as input. The vision processing module transmits an output from execution of one or more of the 3D vision processing algorithms to at least one of: the processor, the memory module, or the network interface.

Abstract: Described are methods and systems for generating a video stream of a scene including one or more objects. A sensor captures images of objects in a scene. A server coupled to the sensor, for each image, generates an initial 3D model for the objects and an initial 3D model of the scene. The server, for each image, captures pose information of the sensor as the sensor moves in relation to the scene or as the objects move in relation to the sensor. A viewing device receives the models and the pose information from the server. The viewing device captures pose information of the viewing device as the viewing device moves in relation to the scene. The viewing device renders a video stream on a display element using the received 3D models and at least one of the pose information of the sensor or the pose information of the viewing device.

Abstract: Described are methods and systems for real-time remote avatar creation and animation control. A sensor device captures images of non-rigid objects in a scene. A server coupled to the sensor device generates an initial 3D model for each of the non-rigid objects in the scene using the images. The server detects landmark points on the non-rigid objects using the initial 3D model. The server generates a control point animation map for the 3D model using the detected points. The server applies the animation map to the 3D model to generate a mapped 3D model. A viewer coupled to the server receives (i) the mapped 3D model and (ii) tracking information associated with the objects, including a model pose and deformation of the landmark points. The viewer modifies the mapped 3D model using the tracking information, and renders a video stream on the viewer using the modified 3D model.

Abstract: Described are methods and systems for combining sparse two-dimensional (2D) and dense three-dimensional (3D) tracking of objects. A 3D sensor coupled to a computing device captures 3D scans of a physical object, including related pose information, and one or more color images corresponding to each 3D scan. For each 3D scan: the computing device establishes initial sparse 2D correspondences between a current loose frame and one or more of: a last tracked loose frame or a current keyframe. The computing device determines an approximate pose based upon the initial sparse 2D correspondences. The computing device establishes initial dense 3D correspondences between the current loose frame and an anchor frame, and combines the initial sparse 2D correspondences and the initial dense 3D correspondences to generate an estimated pose of the object in the scene.

Abstract: Described herein are methods and systems for closed-form 3D model generation of non-rigid complex objects from scans with large holes. A computing device receives (i) a partial scan of a non-rigid complex object captured by a sensor coupled to the computing device; (ii) a partial 3D model corresponding to the object, and (iii) a whole 3D model corresponding to the object, wherein the partial 3D scan and the partial 3D model each includes one or more large holes. The device performs a rough match on the partial 3D model and changes the whole 3D model using the rough match to generate a deformed 3D model. The device refines the deformed 3D model using a deformation graph, reshapes the refined deformed 3D model to have greater detail, and adjusts the whole 3D model according to the reshaped 3D model to generate a closed-form 3D model that closes holes in the scan.

Abstract: A film application apparatus includes a first base configured to couple a film material and a second base rotatably coupled to the first base. The first base defines an opening and two through holes on opposite side of the first base, the through holes communicate with the opening. The second base defines a receiving chamber and the receiving chamber is configured for accommodating a work piece. The film application apparatus further includes a pressing component inserted through the first base, the pressing component penetrating through the opening from the two through holes for pressing the film material against to a face of the work piece.