Ricoh Company, Ltd.

Other

Gang Qiao

Xin Wang

Qian Wang

Shengyin Fan

Jiadan Zhu

Ping Li

Jingyuan Zhang

Mingming Sun

Yue Feng

Zhongwei Cheng

Kefeng Meng

Qiaofei Wang

The application provides a character correction method and apparatus, a device, and a storage medium, where the method including: obtaining position information of a click operation of a user on a terminal screen, and obtaining feature information of the click operation; determining distance information between the position information and each key on the terminal screen; determining transition probability information from a character indicated by a history click operation to a character corresponding to each key; determining a character prediction result according to the feature information, the distance information and the transition probability information, where the character prediction result comprises a probability score that the character indicated by the click operation belongs to the character corresponding to each key; and determining the character with a highest probability score as a correction character corresponding to the click operation.

Character correction method and apparatus, device, and storage medium

A method and an apparatus for detecting an abnormal situation are disclosed. The method includes detecting whether a first target exists in an obtained image; recognizing whether the first target holds an object, when the first target exists in the image; obtaining motion information of the object, when the first target holds the object; and determining, based on the motion information of the object, whether the abnormal situation exists.

Method and apparatus for detecting abnormal situation, and non-transitory computer-readable recording medium

A method and an apparatus for detecting an interest degree of a crowd in a target position are disclosed. The interest degree detection method includes projecting a depth image obtained by photographing onto a height-top-view, the depth image including the crowd and the target position; dividing the height-top-view into cells; determining density of the crowd in each cell; determining a moving speed and a moving direction of the crowd in each cell; determining orientation of the crowd in each cell; and determining, based on the density, the moving speed, the moving direction and the orientation of the crowd, the interest degree of the crowd in each cell in the target position. According to this method, the interest degree of the crowd in the target position can be detected accurately, even at a crowded place where it is difficult to detect and track a single person.

Method for detecting crowd density, and method and apparatus for detecting interest degree of crowd in target position

Method, device, and non-transitory computer-readable medium detecting a gathering of objects based on stereo vision are disclosed, and the method comprises steps of obtaining current and prior images and a corresponding depth map; extracting foreground pixels corresponding to detection objects from the current and prior images, and projecting the foreground pixels onto a ground surface to acquire a foreground projection image including foreground projection blocks; conducting, based on image feature differences of the foreground pixels between the current and prior images, projection onto the ground surface to acquire moving foreground projection blocks; utilizing the moving foreground projection blocks to erode the foreground projection blocks to obtain still foreground projection blocks; and determining, based on the still foreground projection blocks, whether the gathering of objects exists.

Method and device for detecting gathering of objects based on stereo vision as well as non-transitory computer-readable medium

A method and a system for updating a background model based on depth are disclosed. The method includes receiving, in response to the occurrence of a predetermined background updating condition, one or more depth images captured after a time when the predetermined background updating condition occurs; obtaining, based on an original background model, foreground images in the one or more captured depth images, which are newly added compared with a depth image at the time when the predetermined background updating condition occurs; for each of foreground pixels in each of the newly added foreground images, comparing a current depth value with a previous depth value before the time when the predetermined background updating condition occurs; and updating, when the current depth value is greater than the previous depth value, the original background model as the updated background model by using the foreground pixel in the newly added foreground image.

Method and system for updating background model based on depth

Disclosed are a shadow detection method and device. The method includes a step of obtaining a depth/disparity map and color/grayscale image from a two-lens camera or stereo camera; a step of detecting and acquiring plural foreground points; a step of projecting the acquired plural foreground points into a 3-dimensional coordinate system; a step of carrying out, in the 3-dimensional coordinate system, a clustering process with respect to the projected plural foreground points so as to divide the projected plural foreground points into one or more point clouds; a step of calculating density distribution of each of the one or more point clouds by adopting a principal component analysis algorithm so as to obtain one or more principal component values of the corresponding point cloud; and a step of determining, based on the one or more principal component values, whether the corresponding point cloud is a shadow.

Growing community of inventors

Beijing, China

Gang Qiao