A three-dimensional imaging system includes an image intensification subsystem and an illumination subsystem that are both capable of operating with sinusoidal or pulsed waveforms in accordance with phase-measuring or flash modes of operation, respectfully, of the three-dimensional imaging system.

A three-dimensional imaging system includes an image intensification subsystem and an illumination subsystem that are both capable of operating with sinusoidal or pulsed waveforms in accordance with phase-measuring or flash modes of operation, respectfully, of the three-dimensional imaging system.

The processor calculates a first phase difference between a first light and a first reflection light, and a second phase difference between a second light and a second reflection light, generates a first distance image and a second distance using the first phase difference and the second phase difference, respectively, generates a first intensity image and a second intensity image for each of pixel of the first distance image and pixel of the second distance image, respectively, compares light receiving intensity for each pixel of the first intensity image with light receiving intensity for a corresponding pixel of the second intensity image, selects a pixel from the first distance image and a corresponding pixel of the second distance image based on the comparison, and generates a synthesized distance image using the selected pixels.

In accordance with embodiments of the present disclosure, an information handling system may include a processor and a non-transitory computer-readable medium embodying a program of instructions. The program of instructions may be configured to, when read and executed by the processor, receive a visible-light image from a visible-light sensor, receive an infrared image from an active infrared sensor, and compare the visible-light image to the infrared image to determine shadow regions of the visible-light image having shadows.

A process generates a lookup table to estimate spatial depth in a visual scene. The process identifies subsets of illuminators of a camera system with image sensors and illuminators. The image sensors are associated with multiple pixels. For each pixel, and for each of multiple depths from the pixel, the process simulates a virtual surface at the depth. For each subset of the subsets of illuminators, the process simulates illumination of the virtual surface from the subset and determines an expected light intensity at the pixel from light reflected from the virtual surface due to the simulated illumination. The process forms intensity information from the expected light intensity determined for the pixel for each of the depths and each of the subsets. The process constructs a lookup table comprising the intensity information. The lookup table associates the intensity information for each pixel with the respective depth and the respective subset.

A process generates a lookup table to estimate spatial depth in a visual scene. The process identifies subsets of illuminators of a camera system with image sensors and illuminators. The image sensors are associated with multiple pixels. For each pixel, and for each of multiple depths from the pixel, the process simulates a virtual surface at the depth. For each subset of the subsets of illuminators, the process simulates illumination of the virtual surface from the subset and determines an expected light intensity at the pixel from light reflected from the virtual surface due to the simulated illumination. The process forms intensity information from the expected light intensity determined for the pixel for each of the depths and each of the subsets. The process constructs a lookup table comprising the intensity information. The lookup table associates the intensity information for each pixel with the respective depth and the respective subset.

A method includes capturing a first image of a scene, detecting a face in a section of the scene from the first image, and activating an infrared (IR) light source to selectively illuminate the section of the scene with IR light. The IR light source includes an array of IR light emitting diodes (LEDs). The method includes capturing a second image of the scene under selective IR lighting from the IR light source, detecting the face in the second image, and identifying a person based on the face in the second image.

A method includes capturing a first image of a scene, detecting a face in a section of the scene from the first image, and activating an infrared (IR) light source to selectively illuminate the section of the scene with IR light. The IR light source includes an array of IR light emitting diodes (LEDs). The method includes capturing a second image of the scene under selective IR lighting from the IR light source, detecting the face in the second image, and identifying a person based on the face in the second image.

Methods and systems for determining rotation and clipping parameters for images of unit load devices (ULDs) are disclosed herein. An example method includes capturing a set of image data featuring a ULD. The example method may further include locating a fiducial marker proximate to the ULD within the set of image data. The example method may further include cropping the set of image data, based upon the located fiducial marker, to generate a set of marker point data and a set of floor point data. The example method may further include rotating the set of image data based upon the set of marker point data and the set of floor point data, and clipping the rotated set of image data based upon the set of marker point data and the set of floor point data.

Methods and systems for determining rotation and clipping parameters for images of unit load devices (ULDs) are disclosed herein. An example method includes capturing a set of image data featuring a ULD. The example method may further include locating a fiducial marker proximate to the ULD within the set of image data. The example method may further include cropping the set of image data, based upon the located fiducial marker, to generate a set of marker point data and a set of floor point data. The example method may further include rotating the set of image data based upon the set of marker point data and the set of floor point data, and clipping the rotated set of image data based upon the set of marker point data and the set of floor point data.