A display control device for a vehicle includes: a display controller that displays a predetermined display image on a windshield of the vehicle; a visibility reducing area detector that detects a presence or an absence of a visibility reducing area which reduces a visibility of the display image on the windshield; and a gaze detector that detects a gaze of a driver. When the display image overlaps with the visibility reducing area and the driver does not keep the gaze on the display image, the display controller moves the display image to an outside of the visibility reducing area.

This disclosure provides an apparatus and method for performing object detection based on images captured by a fisheye camera and an electronic device. The apparatus includes a memory and a processor coupled to the memory. The processor according to an embodiment is configured to: project an original image captured by the fisheye camera onto a cylindrical or spherical projection model, and perform reverse mapping to obtain at least two reversely mapped images, angles of view of the at least two reversely mapped images being towards different directions, detect objects in the reversely mapped images, respectively, and detect an object that is the same among the objects detected in the reversely mapped images. According to this disclosure, information in the wide field of view images obtained by capturing by the fisheye camera may be fully utilized.

The invention provides an autonomous vehicle with a video camera that merges images taken a different light levels by replacing saturated parts of an image with corresponding parts of a lower-light image to stream a video with a dynamic range that extends to include very low-light and very intensely lit parts of a scene. The high dynamic range (HDR) camera streams the HDR video to a HDR system in real time—as the vehicle operates. As pixel values are provided by the camera's image sensors, those values are streamed directly through a pipeline processing operation and on to the HDR system without any requirement to wait and collect entire images, or frames, before using the video information.

A method of operating an apparatus using a control system that includes at least one neural network. The method includes receiving an input value captured by the apparatus, processing the input value using the at least one neural network of the control system implemented on first one or more solid-state chips, and obtaining an output from the at least one neural network resulting from processing the input value. The method may also include processing the output with another neural network implemented on solid-state chips to determine whether the output breaches a predetermined condition that is unchangeable after an initial installation onto the control system. The aforementioned another neural network is prevented from being retrained. The method may also include the step of using the output from the at least one neural network to control the apparatus unless the output breaches the predetermined condition. Similar corresponding apparatuses are described.

A trailer-camera system for a vehicle coupled to a trailer. The system includes a first plurality of cameras configured to capture a video image including a region of interest surrounding the trailer, a second plurality of cameras configured to capture a video image including a region of interest surrounding the vehicle, and an electronic processor. The processor is configured to receive images from the first and second plurality of cameras and determine a trailer angle. The processor is further configured to generate a first 360-degree image view of an area surrounding the trailer based on an image stitching of the first plurality of images, generate a second 360-degree image view of an area surrounding the vehicle based on an image stitching of the second plurality of images, and generate a combined 360-degree image view from the first and second views based on the trailer angle.

A method for multi-camera monocular depth estimation using pose averaging is described. The method includes determining a multi-camera photometric loss associated with a multi-camera rig of an ego vehicle. The method also includes determining a multi-camera pose consistency constraint (PCC) loss associated with the multi-camera rig of the ego vehicle. The method further includes adjusting the multi-camera photometric loss according to the multi-camera PCC loss to form a multi-camera PCC photometric loss. The method also includes training a multi-camera depth estimation model and an ego-motion estimation model according to the multi-camera PCC photometric loss. The method further includes predicting a 360° point cloud of a scene surrounding the ego vehicle according to the trained multi-camera depth estimation model and the ego-motion estimation model.

A vehicular camera system includes a camera module having an imager assembly, a main circuit board and a camera housing. The imager assembly includes (i) an imager disposed on an imager circuit board and (ii) a lens holder having a lens assembly that includes a lens barrel accommodating a lens. The imager assembly includes a flexible ribbon cable that electrically connects to an electrical connector at a multilayered PCB of the main circuit board. The camera housing includes an upper cover and a lower cover and includes a forward portion and a rearward portion. The main circuit board is accommodated within the forward and rearward portions, and the imager is disposed at the rearward portion and is not disposed at the forward portion of the camera housing. The lens holder is attached at the upper cover of the camera housing.

Proposed are a device provided in a vehicle and a method for controlling same. A device provided in a vehicle according to one embodiment of the present disclosure comprises: a first module which executes a first application and outputs first video data corresponding to the first application; and a second module which is wired or wirelessly connected to the first module and outputs video data, which is the same as the first video data, at a first timing. The second module is designed to output second video data which is different from the first video data in response to, for example, an event which has occurred at a second timing after the first timing.

A surround view monitoring system and a method for providing the same, including a plurality of registration cameras, each mounted on a vehicle and photographing different areas around the vehicle; a depth camera that acquires distance information with respect to an obstacle existing around the vehicle; an image synthesis unit that generates a synthesis image by synthesizing images photographed by the plurality of registration cameras, and displays the distance information with respect to the obstacle acquired by the depth camera on an obstacle existing in the synthesis image; and an image control unit that displays the synthesized synthesis image on a display device are disclosed.

The technology relates to autonomous vehicles that use a perception system to detect objects and features in the vehicle's surroundings. A camera assembly having a ling-type structure is provided that gives the perception system an overall 360° field of view around the vehicle. Image sensors are arranged in camera modules around the assembly to provide a seamless panoramic field of view. One subsystem has multiple pairs of image sensors positioned to provide the overall 360° field of view, while another subsystem provides a set of image sensors generally facing toward the front of the vehicle to provide enhanced object identification. The camera assembly may be arranged in a housing located on top of the vehicle. The housing may include other sensors such as LIDAR and radar. The assembly includes a chassis and top and base plates, which may provide EMI protection from other sensors disposed in the housing.