There is provided a vehicle system including a sensing unit, a processing unit, a control unit and a display unit. The sensing unit is configured to capture an image frame containing an eyeball image from a predetermined distance. The processing unit is configured to calculate a pupil position of the eyeball image in the image frame and generate a drive signal corresponding to the pupil position. The control unit is configured to trigger a vehicle device associated with the pupil position according to the drive signal. The display unit is configured to show information of the vehicle device.

There is provided a vehicle system including a sensing unit, a processing unit, a control unit and a display unit. The sensing unit is configured to capture an image frame containing an eyeball image from a predetermined distance. The processing unit is configured to calculate a pupil position of the eyeball image in the image frame and generate a drive signal corresponding to the pupil position. The control unit is configured to trigger a vehicle device associated with the pupil position according to the drive signal. The display unit is configured to show information of the vehicle device.

Various embodiments include systems and methods of arthropod detection using an electronic arthropod detection device. The electronic arthropod detection device may scan a surface or a subject using a terahertz sensor that is sensitive to a terahertz band of electromagnetic radiation to detect the presence or likely presence of an arthropod in a region of interest (ROI). A camera sensitive to a visible band of electromagnetic radiation captures at least one image and provides the image(s) to an object detection model in response to determining that an arthropod is or is likely present in the ROI. A processor may initiate an arthropod detected procedure in response to detecting an arthropod in the ROI.

A neural network image processing apparatus arranged to acquire images from an image sensor and to: identify a ROI containing a face region in an image; determine at plurality of facial landmarks in the face region; use the facial landmarks to transform the face region within the ROI into a face region having a given pose; and use transformed landmarks within the transformed face region to identify a pair of eye regions within the transformed face region. Each identified eye region is fed to a respective first and second convolutional neural network, each network configured to produce a respective feature vector. Each feature vector is fed to respective eyelid opening level neural networks to obtain respective measures of eyelid opening for each eye region. The feature vectors are combined and to a gaze angle neural network to generate gaze yaw and pitch values substantially simultaneously with the eyelid opening values.

Embodiments of the present application disclose a fingerprint identification apparatus and an electronic device. The fingerprint identification apparatus is used to be disposed under a display screen and includes a first filter layer and a fingerprint sensor, and the first filter layer is disposed above the fingerprint sensor, the first filter layer includes a plurality of first filter units, and the plurality of first filter units are disposed in a region of the first filter layer corresponding to an edge region of the fingerprint sensor; sensing units of the edge region of the fingerprint sensor are configured to receive a light signal returned by a finger above the display screen and filtered by the plurality of first filter units; and sensing units of a middle region of the fingerprint sensor are configured to receive a light signal returned by the finger, to generate a fingerprint image of the finger.

An interactive exercise system includes an exercise machine having a display able to present videos, a three-dimensional camera system, and local processing system able to provide pose estimation based on data from the three-dimensional camera system. The system also includes a communication module for connection to a cloud processing system, with the cloud processing system supporting exercise related analytics including those based on pose estimation provided by the local processing system.

A psychological state display system includes a near-infrared light source that outputs outside light toward a plurality of persons, the output light including a first near-infrared radiation having a wavelength of greater than or equal to 780 nm and less than 2,500 nm; an imaging device that receives the first near-infrared radiation included in the output light outputted and captures an infrared image of the plurality of persons; a generation device that, using a trained machine learning model that receives an input of the infrared image captured and outputs a psychological state of at least one person among the plurality of persons indicated by the infrared image, generates psychological data indicating the psychological state; and a display device that displays a change over time in the psychological data generated.

A method for using infrared data analysis and image analysis for robust action recognition in a retail environment may include receiving infrared data captured using one or more infrared sensors from a retail environment; receiving at least one image captured using at least one image sensor from the retail environment; analyzing the infrared data and the at least one image to detect an action performed in the retail environment; and providing information based on the detected action.

A method for triggering image processing based on infrared data analysis may include receiving first infrared input data captured using a first group of infrared sensors; analyzing the first infrared input data to detect an engagement of a person with a retail shelf; receiving second infrared input data captured using a second group of infrared sensors after the capturing of the first infrared input data; analyzing the second infrared input data to determine a completion of the engagement of the person with the retail shelf; in response to the determined completion of the engagement of the person with the retail shelf, analyzing an image of the retail shelf captured using an image sensor after the completion of the engagement of the person with the retail shelf; and using the analysis of the image to determine a state of the retail shelf.

A method for triggering image processing based on vibration data analysis may include receiving vibration data captured using a vibration sensor mounted to a shelving unit including; analyzing the vibration data to determine whether a vibration is a result of an engagement of a person with a retail shelf; in response to a determination that the vibration is the result of the engagement of the person with the retail shelf, triggering analysis of an image of captured after the beginning of the engagement of the person with the retail shelf; in response to a determination that the vibration is not the result of the engagement of the person with the retail shelf, forgoing triggering the analysis of the image; and providing information based on a result of the analysis of the image.