The present disclosure provides various approaches for smart area monitoring suitable for parking garages or other areas. These approaches may include ROI-based occupancy detection to determine whether particular parking spots are occupied by leveraging image data from image sensors, such as cameras. These approaches may also include multi-sensor object tracking using multiple sensors that are distributed across an area that leverage both image data and spatial information regarding the area, to provide precise object tracking across the sensors. Further approaches relate to various architectures and configurations for smart area monitoring systems, as well as visualization and processing techniques. For example, as opposed to presenting video of an area captured by cameras, 3D renderings may be generated and played from metadata extracted from sensors around the area.

A wiper is controlled to sweep a surface area, e.g., a portion of a windshield, in front of a camera, e.g., a camera mounted inside a vehicle. An image captured from the camera after the wiper completes, e.g., immediately completes, the sweep of the surface area in front of the camera is used in generating a depth map. In some embodiments a first wiper is controlled to clear a surface area in front of a first camera while a second wiper is controlled to clear a surface area in front of second camera at the same time, and the first and second cameras are synchronized to initiate image capture at the same time, capturing images through recently cleared area, and the captured images are used to generate a depth map. A vehicle control operation, e.g., a direction, braking or speed control operation is performed based on the depth map.

A key identification system is provided. The key identification system comprises an imaging system to capture an image of a master key, and a logic to analyze the captured image. The imaging system may be capture an image of a groove in the master key from an angle between perpendicular and parallel to the blade of said master key. The logic analyzes the captured image to compare characteristics of the groove with groove characteristics of known key blanks to determine the likelihood of a match between the master key and a known key blank. The key identification system may further compensate for displacement or orientation of the master key with respect to the imaging system when analyzing characteristics of the groove.

The technology disclosed relates to coordinating motion-capture of a hand by a network of motion-capture sensors having overlapping fields of view. In particular, it relates to designating a first sensor among three or more motion-capture sensors as having a master frame of reference, observing motion of a hand as it passes through overlapping fields of view of the respective motion-capture sensors, synchronizing capture of images of the hand within the overlapping fields of view by pairs of the motion-capture devices, and using the pairs of the hand images captured by the synchronized motion-capture devices to automatically calibrate the motion-capture sensors to the master frame of reference frame.

An optical structure, a display substrate and a display device are provided. The optical structure includes a first medium layer being transparent and an opaque layer which is arranged on the first medium layer and includes a plurality of vias. The optical structure is configured to allow light rays passing through each of the plurality of via to project to a corresponding light ray receiving area respectively.

A method and apparatus for controlling an image acquisition device are provided. The method includes that: multiple images photographed by multiple image acquisition devices are acquired; an active image acquisition device and an inactive image acquisition device in the multiple image acquisition devices are determined according to the multiple images; the active image acquisition device is controlled to photograph a first image by using a first configuration, and the inactive image acquisition device is controlled to photograph a second image by using a second configuration; the first image transmitted by the active image acquisition device is acquired, and the second image transmitted by the inactive image acquisition device is acquired, and a bandwidth required by the active image acquisition device to transmit the first image is greater than a bandwidth required by the inactive image acquisition device to transmit the second image.

A processor-implemented liveness detection method includes: obtaining an initial image using a dual pixel sensor; obtaining a left image and a right image from the initial image; and detecting liveness of an object included in the initial image using the left image and the right image.

Embodiments of the present invention provide a display panel, including a display region, wherein the display region includes an iris recognition region; the display panel further includes a light conversion layer disposed in the iris recognition region, the light conversion layer is configured to convert visible light incident on the light conversion layer into infrared light, and the infrared light is emitted from a display side of the display panel.

An optical scanner captures a plurality of images from a plurality of image-capture devices. In response to the activation signal, an evaluation phase is executed, and in response to the evaluation phase, an acquisition phase is executed. In the evaluation phase, a first set of images is captured and processed to produce a virtual frame comprising a plurality of regions, with each region containing a reduced-data image frame that is based on a corresponding one of the plurality of images. Also in the evaluation phase, attributes of each of the plurality regions of the virtual frame are assessed according to first predefined criteria, and operational parameters for the acquisition phase are set based on a result of the assessment. In the acquisition phase, a second set of at least one image is captured via at least one of the plurality of image-capture devices according to the set of operational parameters.

A method for analyzing an interaction between a sample surface and a drop of liquid comprises applying the drop of liquid to the sample surface and illuminating the drop of liquid using at least two light sources. The at least two light sources are each arranged at a light source position surrounding the drop of liquid. Light reflected from the drop of liquid detecting and a sensor position on a sensor of a camera is determined for each detected light reflection. Light source positions are assigned to individual light source positions. A position of the drop of liquid is calculated relative to the sensor and an item of size information of the drop of liquid is determined. The position and the item of size information are calculated from the pairs of one sensor position and one associated light source position.