An image processing system includes: a receiving unit configured to receive an input of a plurality of image frames constituting a video from an imaging apparatus; a detection unit configured to detect a feature point included in an image frame to be processed in the plurality of image frames; and an output unit configured to output an output image obtained by superimposing an image frame to be processed of an area detected as a feature point on a background image generated from at least some of a plurality of image frames.

A joint position estimation device including a memory, and a processor connected to the memory. The processor executes a process including estimating, by a first DNN for which a first parameter determined by learning of the first DNN has been set, a body part region of the animal with respect to input image to be processed; and estimating, by the second DNN for which a second parameter determined by learning of the second DNN has been set, a first joint position and a second joint position in each of the body part region estimated by the first DNN and a plural body parts region in which a plurality of the body part regions are connected.

A method for controlling a terminal apparatus includes acquiring a first gesture image; determining a central coordinate of a gesture in the first gesture image; determining a controlling range in which the gesture has control over the terminal apparatus, based on the central coordinate of the gesture in the first gesture image; and controlling a control object in the controlling range to execute an operation based on a control instruction corresponding to the gesture.

There is provided with an image processing apparatus. A target image including an object, for a predetermined imaging range, is obtained. A background image, which is obtained from a selected image selected from a captured image for the predetermined imaging range based on brightness of the target image, is obtained. A region of the object in the target image based on the background image is obtained.

The technology disclosed attenuates spatial crosstalk from sequencing images for base calling. In particular, the technology disclosed accesses an image whose pixels depict intensity emissions from a target cluster and intensity emissions from additional adjacent clusters. The pixels include a center pixel that contains a center of the target cluster. Each pixel in the pixels is divisible into a plurality of subpixels. Depending upon a particular subpixel, in a plurality of subpixels of the center pixel, which contains the center of the target cluster, the technology disclosed selects, from a bank of subpixel lookup tables, a subpixel lookup table that corresponds to the particular subpixel. The selected subpixel lookup table contains pixel coefficients that are configured to maximizes a signal-to-noise ratio. The technology disclosed element-wise multiplies the pixel coefficients with the pixels and determines a weighted sum.

Systems and methods for using a mobile device to submit an application for an insurance policy using images of documents captured by the mobile device are provided herein. The information is then used by an insurance company to generate a quote which is then displayed to the user on the mobile device. A user captures images of one or more documents containing information needed to complete an insurance application, after which the information on the documents is extracted and sent to the insurance company where a quote for the insurance policy can be developed. The quote can then be transmitted back to the user. Applications on the mobile device are configured to capture images of the documents needed for an insurance application, such as a driver's license, insurance information card or a vehicle identification number (VIN). The images are then processed to extract the information needed for the insurance application.

An image processing method is provided to be performed by an electronic device. The method includes: obtaining a target image including a text object, and determining a region proposal in the target image corresponding to the text object; obtaining region proposal feature information of the region proposal, and generating an initial mask according to the region proposal feature information; and restoring the initial mask to a target binary mask, determining a mask connection region in the target binary mask, and determining a text image region associated with the text object in the target image according to the mask connection region.

One embodiment is directed to a system for enabling two or more users to interact within a virtual world comprising virtual world data, comprising a computer network comprising one or more computing devices, the one or more computing devices comprising memory, processing circuitry, and software stored at least in part in the memory and executable by the processing circuitry to process at least a portion of the virtual world data; wherein at least a first portion of the virtual world data originates from a first user virtual world local to a first user, and wherein the computer network is operable to transmit the first portion to a user device for presentation to a second user, such that the second user may experience the first portion from the location of the second user, such that aspects of the first user virtual world are effectively passed to the second user.

Described herein is a method for image processing in which a captured image is processed to provide a background image which is updated in accordance with relative movement between foreground and background in successive captured images.

An image privacy perception method based on deep learning, including the following steps: S1, building a privacy classification data set with labeled categories, and training a privacy perception network with a transfer learning method; S2, recognizing a privacy image using a deep convolutional neural network oriented to privacy perception; and S3, extracting an attention profile according to deep convolutional features of the neural network, and locating an attention focusing region to complete the perception of an image privacy region. The method has the following beneficial effects: by completing end-to-end training and testing based on the deep neural network, the privacy image can be accurately distinguished with the privacy region located, facilitating the selective protection of the privacy information in the image.