Abstract: A method and an apparatus for generating a three-dimensional point cloud image, a computer device and a storage medium. The method comprises: detecting three-dimensional shape coordinates of a three-dimensional object in an infrared camera coordinate system; detecting three-dimensional marker coordinates of the marker set in a marker measurement coordinate system at the same time; obtaining, according to a pre-stored first conversion relationship and a second conversion relationship parameter, three-dimensional color coordinates in the infrared camera coordinate system on the basis of the three-dimensional marker coordinates in the marker measurement coordinate system; and generating a three-dimensional point cloud image of the three-dimensional object in the infrared camera coordinate system by combining the three-dimensional shape coordinates and the three-dimensional color coordinates of the three-dimensional object in the infrared camera coordinate system.

Abstract: The invention relates to the field of battery swap technologies, and specifically provides a detection method for battery swap in a battery swap station. The invention aims to solve the following problem: Potential safety risks are caused by no prevention of a foreign matter on an upper surface of a battery, a damage on a battery in a process of battery swap, and no prevention of circulation of a battery with a damaged lower surface in a battery swap station, because a battery surface is not monitored before and after battery mounting in existing battery swap stations.

Abstract: An automated camera system and method are provided that are configured to search for an object emitting or reflecting a certain wavelength of light. The camera can be infrared, electro-optical, or otherwise. Image processing software is configured to isolate pixel groups in each image, wherein those pixel groups fit a wavelength or color patterns of an object being searched. The system also includes processing methods for determining the relative location of the object (GPS or other) based upon the location of the camera and the field of view of the camera. Materials can also be used to tag the object so that the object is easier to find in adverse lighting conditions. Alternatively, the tag can be a wavelength that only one group of searchers knows about, and hence the object can remain relatively hidden from others. The system can be readily mounted in an aircraft or other vehicle so that large areas can be scanned and searched.

Abstract: Various embodiments of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for monitoring a user's movement in real-time and providing or augmenting stimulation. For example, various embodiments provide techniques generating movement prediction profiles using movement prediction machine learning models and for use in conjunction with wearable devices.

Abstract: Embodiments are disclosed for generating an instant mask from polarized input images.

Abstract: A method of detecting a blemish in a digital camera includes capturing a digital image of a white area by the digital camera; reducing resolution of the digital image by grouping pixels of the digital data into a matrix of a plurality of data blocks; and comparing a luminance value of each of the plurality of data blocks to an average luminance value of other data blocks of the plurality of data blocks within a predetermined region to determine if each of the plurality of data blocks is a potentially bad data block.

Abstract: A cleaning wizard monitors and provides feedback for cleaning of medical equipment to ensure that cleaning is performed based on best practices. The cleaning wizard receives a video stream comprising an item of medical equipment and inputs a first set of video frames from the video stream into a first machine learning model. The first machine learning model is trained to output whether the first set of video frames corresponds to activity that initiates a cleaning protocol for the item of medical equipment. Responsive to the cleaning protocol being initiated, the cleaning wizard inputs a second set of video frames into a second machine learning model trained to output whether the second set of frames meets criteria of the cleaning protocol. Responsive to all criteria of the cleaning protocol being met, the cleaning wizard transmits a notification to an operator that the cleaning protocol is complete.

Abstract: An inspection machine includes image sensors that image a sheet, a lighting device that irradiates the sheet with light, and an image processing device that generates an image of an object from outputs of the image sensors. The image processing device generates captured images that include an image in a predetermined range of the sheet in common based on the outputs from the image sensors. The image processing device extracts images of the object on the sheet for each of the generated captured images. The image processing device associates the extracted images of the object with each other based on a feature amount of the object reflected in the images. The image processing device combines the associated images of the object with each other.

Abstract: In particular embodiments, a computing system may receive a video comprising a plurality of image frames. The system may generate, for each image frame in the video, an initial depth map using a machine-learning model. The system may compute a misalignment error indicating depth misalignments in initial depth maps using a reprojection technique. The system may generate, for each image frame in the video, an optimized camera pose and a flexible deformation spline associated with the image frame to minimize the misalignment error. The system may generate, for each image frame in the video, a refined depth map by adjusting the initial depth map associated with the frame using the flexible deformation spline associated with the image frame.

Abstract: Disclosed is a substrate treating apparatus. The substrate treating apparatus includes an imaging unit that photographs loci of the one or more discharge liquids discharged from the plurality of nozzles, and an inspection unit that calculates impact points of the one or more discharge liquids discharged from the plurality of nozzles and determines whether the impact points of the one or more discharge liquids discharged from the plurality of nozzles are normal. The inspection unit includes an image synthesizing unit that synthesizes a plurality of images captured by the imaging unit, a pre-processing unit that pre-processes image data generated through the image synthesizing unit, and a calculation unit that calculates whether the impact points of the one or more discharge liquids discharged from the plurality of nozzles are normal by comparing the image data pre-processed by the pre-processing unit.

Abstract: A system for an endoscope includes a camera head coupled to an optical channel. The system also includes a light port coupled to the endoscope and configured to receive a first light ray, wherein the first light ray travels through a first optical path along an optical axis of the optical channel. The system also includes a depth measurement module coupled to the endoscope, wherein the depth measurement module is configured to transmit a second light ray through a second optical path along the optical axis. The system also includes an image sensor coupled to the camera head and configured to receive a first set of images pertaining to the first light ray and a second set of images pertaining to the second light ray. The system also includes a processing device configured to use the first and second sets of images to generate one or more 3-D images.

Abstract: The present invention addresses the problem of providing an image processing system that can accurately and efficiently detect a target object even when the positional relationship between an image capturing device and the target object differs between the time of teaching and the time of detection.

Abstract: A method and a device for generating a control signal for a controllable device are provided. The controllable device has an optical position detection system. At least two images of at least one spatial region are generated with at least one optical detection device of the optical position detection system. Markers are identified in the images and the control signal is generated when a relative position between at least two markers changes. In addition, a marker array and a controllable system are provided.

Abstract: The invention provides an English char image recognition method mainly generating a rectangular coordinate frame from a loaded English character image, finding a gravity center in the rectangular coordinate frame, obtaining feature points on the rectangular coordinate frame and around the gravity center, performing one-dimensional convolutional operation and processing on the feature points to generate six layer feature maps, and generating a character recognition result from the six layer feature maps to solve the problem of generating a large amount of computation in conventional two-dimensional recognition operation, thereby achieving an efficacy of reducing recognition equipment costs and enabling fast and accurate recognition.

Abstract: Methods, systems, and apparatus are described herein for tracking objects and managing data. One or more objects may be determined in a first image. An avatar may be generated which is associated with the one or more objects in the first image. A second image may be received. The second image may comprise a change in at least one object of the one or more objects. Based on the change, in the at least one object, the avatar may be updated and the information kept for a predetermined period of time.

Abstract: Provided is a computer-implemented method for training a machine learning (ML) model using labelled and unlabelled data, the method comprising obtaining a set or training data comprising a set of labelled data items and a set of unlabelled data items, training a loss module of the ML model using labels in the set of labelled data items, to generate a trained loss module capable of estimating a likelihood of a label for a data item, and training a task module of the ML model using the loss module, the set of labelled data items, and the set of unlabelled data items, to generate a trained task module capable of making a prediction of a label for input data.

Abstract: An image capture device with processors can execute a set of instructions stored in the system memory to: receive a plurality of time-sequenced images of the animal from the digital image sensor; determine, using an artificial intelligence module, a first birth in process from a first subset of images of the plurality of time-sequenced images of the animal; and determine an interval of time lapse between the first birth in process from the first subset of images of the plurality of time-sequenced images of the animal and a next birth in process from the next subset of images of the plurality of time-sequenced images of the animal, as determined using the artificial intelligence module, and when the interval of time lapse between the first birth in process and the next birth in process exceeds a predetermined amount trigger an action from an alert trigger.

Abstract: A computer-implemented method estimates a course of a roadway in a surrounding area of a vehicle on the basis of a state function describing the course of a roadway. The state function includes a clothoid spline. The method includes providing surrounding-area measurement data describing the course of a roadway at a current position of the vehicle, the surrounding-area measurement data having at least one polynomial function. The method also includes transforming the state function and the surrounding-area measurement data into a common coordinate system. The method further includes adapting the state function on the basis of the surrounding-area measurement data in the common coordinate system.

Abstract: Systems and methods are provided for point cloud compression. An exemplary method includes: receiving point cloud data; quantizing the point cloud data to remove noise to produce quantized point cloud data; generating, using the quantized point cloud data, a plurality of multi-level tiles; performing reordering within the multi-level tiles to optimize a compression rate producing a plurality of reordered multi-level tiles; bit packing the reordered multi-level tiles minimizing bits required to store per tile header data producing a bit packed multi-level tile data; and performing additional compression on the bit-packed multi-level tile data using a first compression algorithm.

Abstract: A method includes obtaining a first image, determining a first target curve of a first region occupied by the first image, where an area of the first region is equal to an area of the first image, determining a target object on the first image, moving the first image to obtain a second image, where a second target curve of a second region in which the target object on the second image is located is close to or overlaps the first target curve, and the second region is an external polygon of the target object, and cropping out an image part that is of the second image and that is moved out of the first region.