Surround view Camera
What is a surround view camera?
A surround-view camera system, also known as a 360-degree camera system, is an automotive feature that utilizes multiple cameras placed around a vehicle to provide a bird's-eye view of the surroundings. It helps drivers with parking, maneuvering in tight spaces, and improving overall situational awareness. The typical setup of a surround-view camera system includes several wide-angle cameras mounted on the front, rear, and sides of the vehicle. These cameras capture the surrounding areas and feed the live video streams to a central processing unit. The processing unit combines and processes the camera feeds to create a composite, stitched image that resembles a top-down view of the vehicle and its surroundings.
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Here are some key features and benefits of a surround-view camera system:
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Enhanced Parking Assistance: The 360-degree view enables drivers to see obstacles, curbs, and other vehicles from a top-down perspective, making parking in tight spots easier and reducing the risk of collisions.
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Improved Safety: The system provides a comprehensive view of blind spots, allowing drivers to detect pedestrians, cyclists, and other objects that may not be visible through mirrors alone.
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Maneuvering Assistance: The stitched image helps drivers navigate through complex maneuvers, such as tight turns, narrow streets, and crowded areas.
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Virtual Top-Down View: The top-down perspective gives drivers a better understanding of their vehicle's position relative to surrounding objects, making it easier to avoid accidental collisions.
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Multiple Viewing Modes: Some surround-view camera systems offer different viewing modes, including front, rear, side, and split-screen views, providing flexibility based on the driver's preferences and requirements.
It's important to note that while a surround-view camera system provides valuable assistance to drivers, it should not replace safe driving practices and the use of other safety features, such as mirrors, sensors, and situational awareness. The implementation and specific features of surround-view camera systems may vary among different vehicle manufacturers. It's recommended to consult the vehicle's user manual or contact the manufacturer for detailed information on the functionality and operation of the specific surround-view camera system installed in a particular vehicle.
How it works
A 360-degree camera system doesn't work with just one camera. Instead, several video cameras are strategically placed around the vehicle, typically on each bumper (within an emblem, in the grille, or near the trunk release), and on either side (underneath the side mirrors, near the corners of the bumpers). When you shift into reverse, or in some vehicles, press a button, the camera array activates. The software interprets the view coming from each camera and stitches them together in one single image on your infotainment screen. The system usually has 4 wide-angle cameras integrated into the car body panels. One camera is in the middle of the front grille. Two more ultra-wide-angle cameras look down from the side view/wing mirrors along the flanks of the car. A fourth is just above the license plate.
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While the minimum number of four cameras can form a 360° vision, some cars can have eight or nine cameras for such application.
Cameras must have the ability to view a vast area, so most of the cameras in such a system would have a wide-angle lens up to 180 degrees.
To avoid distraction, the cameras turn off once the vehicle is moving at traffic speeds. Some vehicles can display the view from only one of those cameras. For example, the passenger-side camera can show a closer view of the wheels to avoid scraping on a curb. Or, the front camera can show what's ahead of the hood, like a parking block or off-road obstacles. Newer 360-degree camera systems take things further. Instead of only providing a top-down or single-side view of the car, they can be adjusted to show different angles of the exterior. It's as if there's a camera on a drone, hovering outside your car, switching to the angle you select.
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Unfortunately, how this tech works isn't as cool as using flying robots. They simply have more advanced software that combines the views from different cameras into adjustable perspectives, with your vehicle illustrated in the middle.
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Panorama image stitching is the process of combining multiple images with overlapping fields of view to create a wide-angle or panoramic image. Here's a high-level overview of how panorama image stitching is typically done:
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Image acquisition: Capture a series of images with overlapping regions. It's important to keep the camera settings consistent across all the images, such as exposure, white balance, and focus.
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Feature detection and matching: Analyze the images to identify distinctive features, such as corners, edges, or key points. Common feature detection algorithms include SIFT (Scale-Invariant Feature Transform) or SURF (Speeded Up Robust Features). Once the features are detected, matching algorithms like the nearest neighbor or RANSAC (Random Sample Consensus) are used to find corresponding features between image pairs.
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Image alignment: Determine the transformation needed to align the overlapping regions of the images. This transformation could involve translation, rotation, and possibly scaling. Common techniques include affine transformation or homography estimation.
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Blending: Once the images are aligned, the next step is to blend them together seamlessly. This involves adjusting the intensity and color values at the overlap regions to create a smooth transition. Techniques like linear blending, gradient-based blending, or multi-band blending are commonly used for this purpose.
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Post-processing: Apply any necessary adjustments or enhancements to the stitched panorama image, such as color correction, exposure compensation, or noise reduction.
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Optional refinement: Depending on the quality of the initial stitching, additional steps can be taken to refine the panorama. This might involve additional feature matching, adjustment of control points, or warping to minimize distortions.
It's worth mentioning that panorama image stitching can be implemented using various software tools and libraries, some of which provide automated stitching algorithms. Popular examples include OpenCV (an open-source computer vision library), PTGui (a dedicated panorama stitching software), or Hugin (an open-source panorama photo stitcher).
Keep in mind that the specific details and algorithms used for panorama image stitching can vary depending on the software or approach chosen, but the overall process usually involves these key step
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Bird Eye view
Creating a 360-degree view involves capturing images or videos from multiple perspectives and combining them to form a seamless panoramic view. Here's a general overview of the process:
Equipment: You'll need a camera capable of capturing a wide field of view and preferably with the ability to capture in all directions. Specialized 360-degree cameras, such as those with multiple lenses or a spherical design, are commonly used. Alternatively, you can use a regular camera and capture multiple images in different directions.
Image/Video Capture: Position the camera in the desired location and capture a series of images or videos, typically at regular intervals or by rotating the camera. Ensure that each capture overlaps with the previous one to facilitate stitching later on.
Image/Video Stitching: Use specialized software or libraries to stitch the captured images or videos together into a seamless 360-degree view. These tools analyze the overlapping areas, align the images, and blend them to create a continuous panoramic view. Popular software for this purpose includes PTGui, Kolor Autopano, or Adobe Premiere Pro with the VR Video plugin.
Post-Processing: After stitching, you can perform additional post-processing to enhance the 360-degree view. This may involve adjusting colors, exposure, or applying filters to improve the overall appearance. Special effects like text overlays or graphics can also be added if desired.
Viewing and Distribution: Once the stitching and post-processing are complete, the resulting 360-degree view can be viewed and distributed through various platforms. Common methods include uploading to 360-degree image/video hosting platforms, such as YouTube, Facebook, or dedicated virtual reality (VR) platforms. Users can then view the 360-degree content using compatible devices like VR headsets, web browsers, or mobile apps.
It's important to note that the specific process and tools used for creating a 360-degree view can vary depending on the equipment and software available to you. Specialized 360-degree cameras often come with their software for stitching and post-processing. Additionally, virtual tour software or platforms may offer a more streamlined workflow for creating interactive 360-degree experiences with hotspots and navigation.
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360 degree camera calibration
Surround view camera systems, also known as 360-degree camera systems, require calibration to ensure accurate and synchronized image stitching from multiple camera perspectives. The calibration process typically involves the following steps:
Camera Mounting: Properly mount the individual cameras on the vehicle at strategic locations to provide a complete view of the vehicle. The cameras are typically placed on the front, rear, and sides of the vehicle, and their positions need to be accurately measured and recorded.
Coordinate System Alignment: Establish a common reference coordinate system for all the cameras. This can be done by placing calibration targets or markers at known positions around the vehicle. The targets can have easily identifiable features, such as circles or corners, that can be used for alignment.
Image Acquisition: Capture a set of calibration images or video sequences from each camera. It's important to have overlapping views among the cameras to enable accurate calibration.
Feature Extraction: Extract corresponding features or key points from the calibration images. These features can be distinctive points or patterns that can be matched across different camera views.
Camera Calibration: Perform camera calibration individually for each camera using the extracted features. This involves estimating the intrinsic parameters (e.g., focal length, principal point) and distortion coefficients (e.g., radial distortion, tangential distortion) of each camera. Calibration techniques like Zhang's method or the OpenCV camera calibration functions can be used.
Stereo Calibration: Perform stereo calibration between pairs of cameras to estimate the relative pose (position and orientation) between them. This step ensures accurate alignment and synchronization of the camera views. The extrinsic parameters (rotation and translation) between camera pairs are calculated using the calibrated intrinsic and corresponding image points.
System Calibration: Combine the individual camera calibrations and stereo calibrations to create a unified calibration for the surround view system. This involves applying transformations to each camera's calibration to align them to a common reference coordinate system.
Image Stitching: Once the system is calibrated, the captured images from the multiple cameras can be stitched together to create a seamless surround view. Image stitching algorithms like feature-based matching, homography estimation, and blending techniques can be employed to achieve accurate and visually pleasing results.
It's worth noting that the calibration process may vary slightly depending on the specific surround-view camera system and software being used. Some systems may have automated calibration procedures or specific calibration software provided by the manufacturer.For precise and accurate calibration, it's recommended to follow the manufacturer's guidelines and instructions provided with the surround-view camera system.
