A lottery ticket pack verification system and method for simultaneously scanning a plurality of picked lottery ticket packs and for determining if the scanned lottery ticket packs are the correct lottery ticket packs based on a lottery ticket pack pick list.

The disclosure provides for a method of controlling one or more sensors on a moving vehicle that is executable by one or more computing devices. The one or more computing devices may detect a first surface at a first location and a second surface at a second location using the one or more sensors. The second surface may be classified as a target of interest. Then the one or more computing devices may determine one or more timing characteristics of the one or more sensors based on a pose or motion of the one or more sensors relative to the first location of the first surface and the second location of the second surface. Then, the one or more computing devices may control the one or more sensors to capture data according to the determined one or more timing characteristics.

An eye-tracking system includes a holographic illuminator and a detector. The holographic illuminator includes a light source configured to provide light and a holographic medium optically coupled with the light source. The holographic medium is configured to receive the light provided from the light source and concurrently project a plurality of separate light patterns toward an eye. The detector is configured to detect a reflection of at least a subset of the plurality of separate light patterns, reflected off the eye, for determining a location of a pupil of the eye. Also disclosed is a method for determining a location of a pupil of an eye with the eye-tracking system that includes the holographic illuminator.

Provided is an information processing apparatus including a processing unit that detects a gaze of a gaze-detection subject on a basis of a polarization image in which an eye of the detection object is imaged.

System and method of implementing a Space Rocket monitoring system for greenhouse gas emissions during rocket flight, employing smartphone video cameras equipped with custom lens attachments, image deconvolution software, machine vision software, and the Tsiolkovsky Rocket Equation. The smartphone is equipped with custom optical lens attachments including a periscope that improves spatial separation (parallax) between camera images and a spectroscope that disperses incoming light from the combustion characteristics of the rocket exhaust according to wavelength and frequency of the light. A combination of image deconvolution software and machine vision software analyzes the images, and matches with existing rocket databases (which may be on remote servers), to identify key rocket characteristics. These are used, in the Tsiolkovsky Rocket Equation to compute rocket fuel expenditures. The software computes greenhouse gas emissions and presents the results using a graphical user interface that presents rocket flight images and corresponding analytics.

The present disclosure describes techniques to improve the resolution and reduce the distortion of structured light projection in miniature wide-angle VCSEL array projection modules used for 3D imaging and gesture recognition. The projector module includes a chief ray corrector optical element, which directs the VCSEL beams along the projector lens chief ray paths. The VCSEL structured illumination projector using the chief ray optical element corrector can create a high resolution, low distortion structured light pattern over an extended distance range greater that the projector lens image focal range. The corrector element is placed close to the VCSEL array. The corrector element can be implemented in various ways including, for example, a refractive lens, diffractive lens or microlens array, depending on the specific application requirements and optical configurations.

Embodiments of the present systems and methods may provide imaging techniques for multidirectional imaging, light conditioning, illumination sequences, or machine learning to create algorithms created from training by other advanced imaging techniques. In an embodiment, a method for generating an image may comprise obtaining an image of an object produced by a camera and generating, from the obtained image produced by a conventional camera, using an artificial intelligence model and imaging process, an output image including additional information similar to additional information present in an image of the object produced by an advanced imaging system.

An image capture device is mounted in a vehicle. The image capture device includes: an image capture unit; and a setting unit that sets an image capture condition for each region of the image capture unit each having a plurality of pixels, or for each pixel, based upon at least one of a state exterior to the vehicle and a state of the vehicle.

An optical fingerprint sensing module for sensing a fingerprint pattern of a finger is provided, wherein the finger is placed on a display panel module, and light is generated by the display panel module and reflected by the finger. The optical fingerprint sensing module includes a circuit board, an image sensor on the circuit board, a frame on the circuit board, a lens embedded in the frame, and an IR filter disposed above the image sensor. The image sensor is located in the frame, and the frame includes anti-infrared material. The lens corresponds to a sensing area of the display panel module. Light emitted from the display panel module is reflected by the finger located in the sensing area and then sequentially propagates through the lens and the IR filter to reach the image sensor.

An apparatus includes a dynamic vision sensor (DVS) configured to output an asynchronous stream of sensor event data, a CMOS image sensor configured to output frames of image data, an inertial measurement unit (IMU), a processor and a memory. The memory contains instructions, which when executed by the processor, cause the apparatus to generate a semantic segmentation of a time-stamped frame, which is based on one or more of an output of the CMOS image sensor, or a synthesized event frame based on an output from the DVS and an output from the IMU over a time interval. The semantic segmentation includes a semantic label associated with a region of the time-stamped frame. When executed, the instructions further cause the apparatus to determine, based on the semantic segmentation, a simplified object representation in a coordinate space, and update a stable semantic map based on the simplified object representation.