Systems, assemblies, and methods for detecting changes in polarization states are described. Example systems may include a light receiving unit including a sensor and a receiving polarizer. The sensor is configured to sense light from a polarized light source deflected through the receiving polarizer by a light directing article. The sensor is configured to generate a signal indicative a received polarization state of light deflected by the light directing articles. Such systems may be coupled to vehicles and may be useful for sensor-detectable signs, indicia, and markings to facilitate automated or assisted vehicular transport.

Disclosed herein are a method of acquiring an image for recognizing a position and a robot implementing the same. In the method and robot, information value concerning movement of the robot is measured to efficiently acquire images including overlapped areas, and lenses of cameras on both sides of the robot are slided in a direction opposite to a direction of movement of the robot based on the measured information value concerning movement.

Described is a method for processing image data to determine if a portion of the imaged environment is exposed to high illumination, such as sunlight. In some implementations, image data from multiple different imaging devices may be processed to produce for each imaging device a respective illumination mask that identifies pixels that represent a portion of the environment that is exposed to high illumination. Overlapping portions of those illumination masks may then be combined to produce a unified illumination map of an area of the environment. The unified illumination map identifies, for different portions of the environment, a probability that the portion is actually exposed to high illumination.

Systems and methods for realizing practical applications of high speed digital image correlation (DIC) for dynamic quantities of interest are provided. In particular, a series of images are captured for a component of interest in which a non-filtered sensor and an analog low-pass filtered sensor are included within the region of interest for the series of images. Displacement signals are obtained for the component of interest, the non-filtered sensor, and the analog low-pass filtered sensor by applying digital image correlation processing to the series of images, which may also be wavelet filtered. Dynamic quantities of interest may be generated and derived from the displacement signals after having been wavelet filtered. Such dynamic quantities of interest based on the wavelet filtered DIC-derived displacement signal may be compared to sensor-derived dynamic quantities of interest to determine if aliasing is or is likely to be present.

A disclosed example to operate a mobile camera includes recognizing a first feature in first sensor data in response to the first feature being detected in the first sensor data; transitioning the mobile camera from a first feature detection state to a second feature detection state in response to the recognizing of the first feature, the mobile camera to operate using higher power consumption in second feature detection state than in the first feature detection state; recognizing a second feature in second sensor data in the second feature detection state; and sending to an external device at least one of first metadata corresponding to the first feature or second metadata corresponding to the second feature.

An imaging system of the present disclosure includes: an event detection device that detects an event; and a controller that controls the event detection device. The controller then controls the detection sensitivity of event detection being performed by the event detection device, on the basis of external information. Further, an object recognition system of the present disclosure includes: an event detection device that detects an event; a controller that controls the detection sensitivity of event detection being performed by the event detection device, on the basis of external information; and a recognition processing unit that performs object recognition in an event, on the basis of an event signal output from the event detection device.

A method (100), a device (600;700) and a system (800) for processing image data representing a scene for extracting features related to objects in the scene using a convolutional neural network are disclosed. Two or more portions of the image data representing a respective one of two or more portions of the scene are processed (S110), by means of a respective one of two or more circuitries, through a first number of layers of the convolutional neural network to form two or more outputs, wherein the two or more portions of the scene are partially overlapping. The two or more outputs are combined (S120) to form a combined output, and the combined output is processed (S130) through a second number of layers of the convolutional neural network by means of one of the two or more circuitries for extracting features related to objects in the scene.

A display device is provided and includes display panel; sensor substrate formed on display panel; and M drive electrodes and detection electrodes extended in direction so as to intersect with M drive electrodes, wherein among M drive electrodes, any of lengths of N first drive electrodes, which are continuously adjacent to one another, is shorter than any of lengths of other N second drive electrodes which are continuously adjacent to one another, and number of detection electrodes which intersect with N first drive electrodes is larger than number of detection electrodes which intersect with N second drive electrodes.

A target detection apparatus is configured to recognize a stationary object present within a detection range of an external sensor based on map information. Next, the target detection apparatus is configured to determine, by checking an image of the stationary object detected by the external sensor against the stationary object recognized from the map information, whether the image of the stationary object detected by the external sensor includes an undetected region. When the undetected region is identified, the target detection apparatus is configured to recognize an undetectable object present between the stationary object and a vehicle.

An object detection system for a vehicle includes a camera vision module and a Lidar module. The camera vision module includes an imaging device viewing to the exterior of the vehicle and operable to capture image data representative of a scene exterior and forward of the vehicle. The Lidar module includes a Lidar device that, with the Lidar module mounted at a front exterior portion of the vehicle, scans a region forward of the vehicle that overlaps with the field of view of the imaging device. Based at least in part on processing of captured image data by an image processor and based at least in part on processing of Lidar data captured by the Lidar device, 3-dimensional and timing information relative to the vehicle of objects present exterior of the vehicle is algorithmically constructed. At least one individual object of the multiple objects is prioritized.