A sensor subsystem for vehicles, such as autonomous driving vehicles, has two network ports for which each network port is connectable to one of two in-vehicle computers (IVCs) for control, configuration, status and data transfers between the sensor subsystem and the two IVCs. The two IVCs can be structured as redundant IVCs. The sensor subsystem can replicate sensor data to the redundant IVCs. The sensor data can be raw image data, encoded image data, processed perception data, or a combination of the data. The two IVCs can be implemented with a modular design with each IVC disposed on a platform separate from the platform on which the second of the two redundant IVCs is disposed. The two IVCs can be replaced separately to reduce repair or replacement cost.

A display apparatus includes display recognition units and a first processing device. Each of the display recognition units includes one or more sub-pixels and a photosensitive sensing device. The photosensitive sensing device is configured to convert reflected light of light emitted from at least one sub-pixel into a first electrical signal, and convert external light containing information entering from a display side into a second electrical signal. The first processing device is connected to photosensitive sensing devices of the display recognition units, and configured to obtain a texture image according to first electrical signals output by the photosensitive sensing devices, and determine the information contained in the external light according to a second electrical signal output by at least one photosensitive sensing device.

A display apparatus includes display recognition units and a first processing device. Each of the display recognition units includes one or more sub-pixels and a photosensitive sensing device. The photosensitive sensing device is configured to convert reflected light of light emitted from at least one sub-pixel into a first electrical signal, and convert external light containing information entering from a display side into a second electrical signal. The first processing device is connected to photosensitive sensing devices of the display recognition units, and configured to obtain a texture image according to first electrical signals output by the photosensitive sensing devices, and determine the information contained in the external light according to a second electrical signal output by at least one photosensitive sensing device.

Described herein are a system and a method for object recognition via a computer vision application, the system including at least the following components: at least one object to be recognized, the object having object specific reflectance and luminescence spectral patterns, a light source which is configured to illuminate a scene including the at least one object, the light source being designed to omit at least one spectral band of a spectral range of light when illuminating the scene, the at least one omitted spectral band being in the luminescence spectral pattern of the at least one object, at least one sensor which is configured to exclusively measure radiance data of the scene in at least one of the at least one omitted spectral band when the scene is illuminated by the light source, a data storage unit, and a data processing unit.

An advance in high-resolution optical metrology has been achieved by the introduction of incoherent holographic imaging. FINCH, an example of incoherent holography, is shown to simplify the process, eliminating many steps in metrology and at the same time increasing throughput, resolution and accuracy of the method. A proposed technique requires only a single image capture with a non-moving camera rather than the capture of multiple stacks of images requiring many camera exposures and movement of the camera or sample in the conventional techniques.

This document describes systems and techniques directed at under-display sensor lamination. In aspects, an electronic device having a mechanical frame designed with a bucket architecture includes an under-display sensor attached to one or more layers of a display panel stack. Such an implementation enables attachment of the under-display sensor to a protective layer, as opposed to attachment of the sensor directly to a display panel, minimizing the risk of delamination, as well as reducing damage to the display panel if delamination occurs and rework is attempted. Further, such an implementation removes the need for a mid-frame architecture, resulting in a thinner and lighter electronic device.

This document describes systems and techniques directed at under-display sensor lamination. In aspects, an electronic device having a mechanical frame designed with a bucket architecture includes an under-display sensor attached to one or more layers of a display panel stack. Such an implementation enables attachment of the under-display sensor to a protective layer, as opposed to attachment of the sensor directly to a display panel, minimizing the risk of delamination, as well as reducing damage to the display panel if delamination occurs and rework is attempted. Further, such an implementation removes the need for a mid-frame architecture, resulting in a thinner and lighter electronic device.

A method includes capturing a frame including a 3D point cloud and a 2D image. A key point is detected in the 2D image, the key point is a candidate to be used as a feature. A 3D patch of a predetermined dimension is created that includes points surrounding a 3D position of the key point. The 3D position and the points of the 3D patch are determined from the 3D point cloud. Based on a determination that the points in the 3D patch are on a single plane based on the corresponding 3D coordinates, a descriptor for the 3D patch is computed. The frame is registered with a second frame by matching the descriptor for the 3D patch with a second descriptor associated with a second 3D patch from the second frame. The 3D point cloud is aligned with multiple 3D point clouds based on the registered frame.

A method, system and computer program product for reducing learning time for a newly installed camera is disclosed. The method includes generating a new unusual activity model for the newly installed camera, based on portion(s) of existing and established unusual activity model(s) built for different older camera(s), where the existing and established unusual activity model(s) relate to at least one same static object appearing within Fields Of Views (FOVs) of the new and older cameras.

A method, system and computer program product for reducing learning time for a newly installed camera is disclosed. The method includes generating a new unusual activity model for the newly installed camera, based on portion(s) of existing and established unusual activity model(s) built for different older camera(s), where the existing and established unusual activity model(s) relate to at least one same static object appearing within Fields Of Views (FOVs) of the new and older cameras.