Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for escape detection and mitigation for aquaculture. In some implementations, a method includes obtaining one or more images that depict one or more fish within a population of fish that are located within an enclosure; providing, to one or more detection models configured to classify fish that are depicted within the images as likely being member or as likely not being member of a type of fish, the one or images; generating, as a result of providing the one or more images to the one or more detection models, a value that reflects a quantity of fish that are depicted in the images that are likely a member of the type of fish; and detecting a condition based at least on the value.

This application provides an image defect detection method. The method includes obtaining a first image and a second image of a flawless image. A third image is obtained from the second image and the first image, and a fourth image is obtained according to the second image and an image to be detected. A fifth image is obtained based on the third image and the second image. A sixth image is obtained based on the third image and the fourth image. A seventh image is obtained from the fifth image and the sixth image. A defect value of the fourth image is obtained according to the third image and the seventh image. A detection result of the fourth image is determined based on the defect value.

An object is to make it possible to accurately estimate the number of movements at a high speed. A generation unit (130) generates an optimization problem for estimating, with respect to each of a plurality of areas, the number of observation targets that move from the area to each of the other areas at each observation time point, as the number of movements, based on observation values and movement probabilities, the observation values indicating, with respect to each area, the number of observation targets that are present in the area at each observation time point, and the movement probabilities indicating, with respect to each area, probabilities of movement from the area to the other areas at each observation time point. A first estimation unit (140) estimates the number of movements by solving the generated optimization problem using a Sinkhorn-Knopp algorithm. A second estimation unit (160) estimates the movement probabilities based on the observation values and the estimated number of movements. An estimation control unit (120) repeats generation of the optimization problem, estimation of the number of movements, and estimation of the movement probabilities until a condition determined in advance is satisfied.

A method for providing an augmented reality service using an AR sticker comprises: a step where a mobile terminal requests, from a server, an AR sticker template enabling a user to edit an AR sticker, and the server transmits the AR sticker template; a step where the mobile terminal directly edits the AR sticker image using the AR sticker template and creates AR content corresponding to the AR sticker image; a step where the server receives the AR sticker image and the AR content from the mobile terminal and stores same in an AR database, and creates an AR sticker including the AR sticker image and the AR content; a step where the mobile terminal receives the AR sticker, transmits the AR sticker to a printer, and requests printing of the AR sticker; and a step where the printer prints the AR sticker and conveys the printed AR sticker.

Enables integration of sensor data with other information on servers such as social media sites to detect, confirm and/or publish events. Sensors may measure values such as motion, temperature, humidity, wind, pressure, elevation, light, sound, or heart rate, etc. Sensor data and event tags may be utilized to curate text, images, video, sound and post the results to social networks, for example in a dedicated feed. Event tags generated by the system may represent for example activity types, players, performance levels, or scoring results. The system may analyze social media postings to confirm or augment event tags. Users may filter and analyze saved events based on the assigned tags. The system may create highlight and fail reels filtered by metrics and by tags. Recommendations may be provided to a user based on analysis of sensor data and other information; recommendations may include for example recommended friends, purchases, or activities.

A system for law enforcement recording that includes: a robotic camera; a position transmitter on the robotic camera; and at least one receiver, where the at least one receiver is adapted to be worn by a user. The robotic camera captures panoramic views surrounding the at least one receiver. The receiver may be worn by the user in the form of an armband or strip placed on a user's hat.

Disclosed is a computer-implemented method of determining a spatial relationship between planning image data and current surface data which leads to improved surface registration accuracy by considering the elasticity and deformability of the tissue. The knowledge about the tissue can be estimated based on type of tissue and atlas information. For the process of generating surface registration points on specific anatomical regions, e.g. the face or forehead, are acquired with a classical navigated pointer or laser pointer. It is also possible to acquire points with surface scanners. Confidence values defining a probability for certain parts of the surface registration points being deformed in comparison to a planning image are read from atlas data and used to compensate for the deformation in the registration between the surface registration points and the planning image in order to render the registration valid.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for escape detection and mitigation for aquaculture. In some implementations, a method includes obtaining one or more images that depict one or more fish within an enclosure; generating, as a result of providing the one or more images to multiple detection models, a value that reflects a quantity of fish that are depicted in the images that are likely a member of each different type of fish; detecting an error condition relating to a possible opening of the enclosure based at least on the value; and in response to detecting the error condition relating to the possible opening of the enclosure, initiating one or more mitigation actions relating to the possible opening.

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for escape detection and mitigation for aquaculture. In some implementations, a method includes obtaining one or more images that depict one or more fish within a population of fish that are located within an enclosure; providing, to one or more detection models configured to classify fish that are depicted within the images as likely being member or as likely not being member of a type of fish, the one or images; generating, as a result of providing the one or more images to the one or more detection models, a value that reflects a quantity of fish that are depicted in the images that are likely a member of the type of fish; and detecting a condition based at least on the value.

A method for determining a postural and visual behavior of a person, the method comprising:—a person image receiving step during which a plurality of images of the person are received,—a context determining step during which the plurality of images of the person are analyzed so as to determine context data representative of the context in which the person is on each image of the plurality of images,—an analyzing step during which the plurality of images of the person are analyzed so as to determine at least one oculomotor parameter of the person,—a postural and visual behavior determining step during which a postural and visual behavior of the person is determined based at least on the at least one oculomotor parameter and the context data.