Generally, a system and method for an automatic detection of referee's decisions during a ball-game match are provided. The method may include receiving a plurality of images of a ball-game field generated during the ball-game match; determining, based on predetermined ball-game rules, a first subset of images of the plurality of images representing a first event that is suspected as a specified rule-based event; determining, based on the predetermine ball-game rules, a second subset of images of the plurality of images that represents a second event, wherein the second event is subsequent to the specified rule-based event according to the predetermined ball-game rules; and analyzing, based on the predetermined ball-game rules, the images of the second subset and further determining, based on the analysis thereof, a referee's decision concerning whether the first even is the specified rule-based event.

A projection device includes a camera that captures an image of a real space in which an object is disposed and a projector that projects an image indicated by video data generated based on the captured image by the camera onto an image capturing region of the camera in the real space. The video data is, for example, a pointing image such as an arrow or a finger point pointing to an object disposed in the real space. The projection device detects the object by image recognition from the captured image and generates video data for displaying a pointing image pointing to the object at a position superimposed on or adjacent to the object. When the image indicated by the video data generated is projected from the projector, the pointing image is displayed at a position superimposed on or adjacent to the object in the real space.

A projection device includes a camera that captures an image of a real space in which an object is disposed and a projector that projects an image indicated by video data generated based on the captured image by the camera onto an image capturing region of the camera in the real space. The video data is, for example, a pointing image such as an arrow or a finger point pointing to an object disposed in the real space. The projection device detects the object by image recognition from the captured image and generates video data for displaying a pointing image pointing to the object at a position superimposed on or adjacent to the object. When the image indicated by the video data generated is projected from the projector, the pointing image is displayed at a position superimposed on or adjacent to the object in the real space.

The present invention relates to a device for assisting in electronic gaming, the device comprising a scanning device. The scanning device comprises a scanning surface, wherein the scanning surface is arranged for throwing a die or dice thereon, the flatbed scanning device being configured for scanning instantaneously an image of the scanning surface. The device also comprises a processor configured for receiving scanning information regarding the image of the scanning surface upon which a die or dice are thrown and programmed for deriving, based on said image, data regarding the dice thrown. The scanning device comprises a detection system whereby the detection area span by the detection elements is maximally 10% smaller than the area span by the scanning surface.

In one embodiment, a computing system is configured to, during a first tracking session, detect first landmarks in a first image of the environment surrounding a user, and determine a first location of the user by comparing detected first landmarks to a landmark database. During a second tracking session, the computing system captures motion data and estimates a second location of the user based on the motion data and first user location. Based on the motion data and first user location, the computing system detects landmarks in a second image at a second location. The system accesses expected landmarks from the landmark database visible at the second location and determines the estimated second location of the user is inaccurate by comparing the expected landmarks with the second landmarks. The computing system re-localizes the user by comparing the landmarks in the landmark database and third landmarks in a third image.

In one embodiment, a computing system is configured to, during a first tracking session, detect first landmarks in a first image of the environment surrounding a user, and determine a first location of the user by comparing detected first landmarks to a landmark database. During a second tracking session, the computing system captures motion data and estimates a second location of the user based on the motion data and first user location. Based on the motion data and first user location, the computing system detects landmarks in a second image at a second location. The system accesses expected landmarks from the landmark database visible at the second location and determines the estimated second location of the user is inaccurate by comparing the expected landmarks with the second landmarks. The computing system re-localizes the user by comparing the landmarks in the landmark database and third landmarks in a third image.

Various implementations disclosed herein include devices, systems, and methods that generate floorplans and measurements using a three-dimensional (3D) representation of a physical environment generated based on sensor data.

Methods and systems are provided for implementing preprocessing operations and augmentation operations upon image datasets transformed to frequency domain representations, including decoding images of an image dataset to generate a frequency domain representation of the image dataset; performing a resizing operation based on resizing factors on the image dataset in a frequency domain representation; performing a reshaping operation based on reshaping factors on the image dataset in a frequency domain representation; and performing a cropping operation on the image dataset in a frequency domain representation. The methods and systems may further include performing an augmentation operation on the image dataset in a frequency domain representation. Methods and systems of the present disclosure may free learning models from computational overhead caused by transforming image datasets into frequency domain representations. Furthermore, computational overhead caused by inverse transformation operations is also alleviated.

Disclosed is a method for recognizing a marine object based on hyperspectral data including collecting target hyperspectral data; preprocessing the target hyperspectral data; and detecting and identifying an object included in the target hyperspectral data based on a marine object detection and identification model, trained through learning of the detection and identification of the marine object. According to the present invention, the preprocessing and processing of the hyperspectral data collected in real time according to a communication state may be performed in the sky or on the ground.

Systems and methods are provided for detecting inaccuracy in a product title, comprising identifying, by running a string algorithm on a title associated with a product, at least one product type associated with the product, predicting, using a machine learning algorithm, at least one product type associated with the product based on the title, detecting an inaccuracy in the title, based on at least one of the identification or the prediction, and outputting, to a remote device, a message indicating that the title comprises the inaccuracy. Running the string algorithm may comprise receiving a set of strings, generating a trie based on the received set of strings, receiving the title, and traversing the generated trie using the title to find a match. Using the machine learning algorithm may comprise identifying words in the title, learning a vector representation for each character n-gram of each word, and summing each character n-gram.