Provided are a method and device for detecting a living-body, and a storage medium. The method includes that: a first image captured by a first camera is acquired, and face detection processing is performed on the first image; a second image captured by a second camera is acquired responsive to detecting that the first image includes a face, where the first camera and the second camera are different types of cameras; and face detection processing is performed on the second image, and responsive to detecting that the second image includes a face, a living-body detection result is obtained based on a matching result of the face detected in the first image and the face detected in the second image.

The disclosure relates to technology for detecting and tracking eye gaze. An apparatus comprises a visible wavelength camera, an infrared (IR) camera, and one or more processors. The one or more processors are configured to generate a three-dimensional (3D) point cloud of a person's face from IR data captured from the IR camera, generate a two-dimensional image of the person's face from visible wavelength data captured from the visible wavelength camera, and detect a symmetry plane of the person's face based on the 3D point cloud and the two-dimensional image. The symmetry plane divides the 3D point cloud into two portions. The one or more processors are further configured to reconstruct the 3D point cloud based on the symmetry plane, and track eye gaze of the person's face based on the reconstructed 3D point cloud.

A fraud confirmation assisting apparatus includes a light source, a reading sensor, and processing circuitry. The light source irradiates an object to be read with light in at least an invisible wavelength range. The reading sensor has sensitivity at least in the invisible wavelength range. The processing circuitry performs a reading operation on the object to be read by a combination of the light source and the reading sensor, and outputs a plurality of pieces of fraud confirmation information based on read information output from the reading sensor by the reading operation.

A fraud confirmation assisting apparatus includes a light source, a reading sensor, and processing circuitry. The light source irradiates an object to be read with light in at least an invisible wavelength range. The reading sensor has sensitivity at least in the invisible wavelength range. The processing circuitry performs a reading operation on the object to be read by a combination of the light source and the reading sensor, and outputs a plurality of pieces of fraud confirmation information based on read information output from the reading sensor by the reading operation.

There is provided a recognition system adaptable to a portable device or a wearable device. The recognition system senses a body heat using a thermal sensor, and performs functions such as the living body recognition, image denoising and body temperature prompting according to detected results.

A device, system and method for the detection and screening of plastic microparticles in a sample is disclosed. A nanoporous silicon nitride membrane is used to entrap plastic microparticles contained in the sample. The sample may be a water sample, an air sample, or other liquid or gas sample. The entrapped plastic microparticles are then heated or otherwise processed on the nanoporous silicon nitride membrane. An imaging system observes the nanoporous silicon nitride membrane with tic entrapped plastic microparticles to determine the type and quantity of the various plastic microparticles that are entrapped on the membrane.

A method, apparatus, and computer-readable medium for sensor-based application deployment, including receiving a sensor analysis application from a remote server over a computer network, executing the sensor analysis application, including communicating with one or more hardware sensors deployed at the local deployment site over a local network and analyzing sensor data received from the one or more hardware sensors over the local network to generate result data, and transmitting the result data to the remote server over the computer network.

A method for image-guided agriculture includes receiving images; processing the images to generate reflectance maps respectively corresponding to spectral bands; synthesizing the reflectance maps to generate a multispectral image including vegetation index information of a target area; receiving crop information in regions of the target area; and assessing crop conditions for the regions based on the identified crop information and the vegetation index information.

The present disclosure provides a method, device and system for detecting a working state of a tower controller, the method includes: collecting voice data of a tower controller, and extracting a keyword from the voice data; acquiring a video image of the tower controller, and acquiring a gaze area of the tower controller from the video image; analyzing and detecting whether the tower controller has correctly accomplished an observation action according to the gaze area of the tower controller and the keyword. The present disclosure implements more efficient and accurate detection on the working state of the tower controller, and at the same time ensures the safety of an aircraft in an airport area and reduces a risk of colliding with other obstacles.

Techniques are provided for multi-modal sensitive recognition. A digital data set for an object is obtained according to a modality, where the digital data set includes digital representations of the object at different values of a dimension of relevance of the modality. A reference location associated with the object is identified. A modal descriptor is derived for the modality according to an implementation of a multi-modal recognition algorithm by deriving a set of feature descriptors for the reference location and at the different values of the corresponding dimension of relevance, calculating a set of differences between the feature descriptors in the set of feature descriptors, and aggregating the set of differences into the modal descriptor. A device is then configured to initiate an action as a function of the modal descriptor.