As an active ranging technology, Light Detection and Ranging (LiDAR) calculates the distance to a target by emitting laser beams and receiving reflected signals. Its high-precision, real-time 3D perception capability provides irreplaceable support for camera focusing systems that is hard to achieve with traditional focusing technologies.

Traditional camera focusing mostly relies on passive methods such as contrast detection and phase detection, which are susceptible to factors like illumination, texture and motion state in complex scenarios. The integration of LiDAR fundamentally compensates for these shortcomings, driving the development of focusing technologies toward higher efficiency, greater reliability and more advanced intelligence.

I. Breaking Through Environmental Limitations and Improving Focus Reliability in Complex Scenarios

The core pain point of traditional focusing technologies lies in their strong dependence on ambient light and target texture, while the active ranging feature of LiDAR allows it to break free from these constraints and achieve stable focusing across all scenarios. In low-light environments (such as nighttime or dim indoor settings), the light signals received by the camera sensor are weak. Contrast detection methods struggle to capture the brightness changes in the image, and the signal accuracy of phase detection methods also drops significantly, which tends to cause issues like slow focusing, blurring, or even loss of focus. In such cases, LiDAR can actively emit laser beams without being affected by the intensity of ambient light. It accurately calculates the distance between the target and the camera by measuring the Time of Flight (ToF) or Direct Time of Flight (DToF), directly providing the focus plane position information for the focusing system, thus ensuring fast and accurate focusing even in low-light conditions.

In low-texture or textureless scenarios (such as solid-color walls, the sky, or smooth metal surfaces), traditional focusing technologies lack detailed image features and cannot determine the focusing state through contrast changes or phase differences, often resulting in the "focus hunting" phenomenon. LiDAR ranging does not rely on the surface texture of the target; as long as the target can reflect laser signals, it can obtain stable distance data, helping the focusing system directly lock onto the focus plane and avoid focusing hesitation. In addition, in extreme lighting conditions such as backlighting or direct glare, the camera image is prone to overexposure or underexposure, leading to the loss of focusing features. However, the ranging signal of LiDAR is independent of the optical imaging signal, enabling it to penetrate light interference and ensure the normal operation of the focusing system.

II. Enhancing Focus Tracking Capability for Dynamic Targets and Reducing the Risk of Motion Blur

For moving targets, traditional focusing systems need to continuously capture image frames and analyze changes in target positions to adjust focusing parameters, which results in a certain response delay. When targets move at high speeds (such as running people, flying birds, and fast-moving vehicles), focusing lag is prone to occur, leading to blurred imaging. LiDAR features an extremely high refresh rate (the refresh rate of some industrial-grade LiDAR can reach over 1000Hz), and it can output real-time 3D position information of targets, including distance, speed, and motion trajectory. This enables the focusing system to predict the motion trend of targets in advance and achieve predictive focusing.

Taking vehicle-mounted cameras as an example, in autonomous driving scenarios, vehicles need to focus on dynamic targets such as pedestrians and other vehicles ahead in real time. Traditional focusing systems may lose focus due to vehicle jolts or sudden lane changes of targets, which affects the accuracy of environmental perception. After the integration of LiDAR and vehicle-mounted cameras, the real-time distance data of targets can be synchronized to the focusing system. The focusing lens adjusts the focal length in advance according to changes in target distance, ensuring that targets remain within the clear focal plane at all times even if they move rapidly in a short period. In the field of film and television shooting, cameras equipped with LiDAR used for motion tracking can accurately track the trajectories of actors or moving objects, avoiding image blurring caused by focusing delay and improving shooting efficiency and the quality of finished footage.

III. Improving Focusing Precision to Support High-Precision Imaging Requirements

The ranging precision of LiDAR has reached the centimeter or even millimeter level, which is far higher than that of traditional focusing technologies, providing core support for scenarios requiring high-precision focusing. In macro photography, when shooting tiny objects (such as insects, chips, and cell slices), a slight deviation in the focusing distance will lead to blurring of the subject, and traditional focusing systems are difficult to accurately control the position of the focal plane. LiDAR can accurately measure the distance between the camera and tiny targets, and combined with auto-focusing algorithms, it can precisely locate the focal plane on the key areas of the target (such as the compound eyes of insects and the circuit patterns of chips), achieving macro imaging with clear details.

In industrial inspection scenarios, cameras are often used for tasks such as product surface defect detection and dimension measurement, where focusing precision directly affects the accuracy of inspection results. For example, when detecting tiny solder defects on circuit boards, inaccurate focusing may lead to missed or false judgments of defects. LiDAR can feed back the precise distance of the target in real time, ensuring that the camera is always focused on the inspection area of the product surface. Combined with high-resolution imaging, it improves the precision and reliability of defect identification. In addition, in UAV aerial photography, LiDAR can be combined with the flight attitude data of the UAV to dynamically compensate for distance changes during flight, enabling the camera to maintain high-precision focusing on ground targets even when moving at high altitudes, thus providing clear image data for surveying, mapping, exploration and other work.

IV. Assisting Multi-Target Focusing Decision-Making and Enabling Intelligent Focus Allocation

When multiple targets exist in the frame, traditional focusing systems usually select the focusing subject based on image contrast or preset rules (such as face priority), which tends to result in focus errors (e.g., prioritizing the background over the foreground subject). LiDAR can acquire 3D point cloud data of the entire scene; it not only obtains the distance information of each target, but also distinguishes the contours and hierarchical relationships of targets through point cloud clustering, helping the focusing system establish a spatial model of the scene and achieve more intelligent focusing decisions.

For example, in group photo scenarios, LiDAR can identify the distances of different people in the frame. Combined with face detection technology, it can prioritize focusing on the face closest to the camera or the preset key person, avoiding focus shift caused by high contrast of background objects. In security surveillance, LiDAR can track multiple moving targets simultaneously and allocate focusing priorities to the camera, ensuring that key targets (such as suspicious individuals) are always in sharp focus while other targets maintain an appropriate depth of field. This not only improves surveillance efficiency, but also reduces the waste of storage resources.

V. Optimizing Focusing Speed and Enhancing User Experience

Traditional focusing systems need to repeatedly adjust the lens focal length and analyze image features to find the optimal focal plane, a process that often takes hundreds of milliseconds or even longer. LiDAR can quickly output the distance information of the scene the moment the camera is activated. The focusing system does not need to perform "exploratory" adjustments, but directly drives the lens to move to the corresponding focal length position based on the distance data provided by LiDAR, thus significantly shortening the focusing time. For example, after consumer-grade smartphones are equipped with LiDAR, their focusing speed can be increased to within 100 milliseconds, delivering an "instant focus" experience. This is particularly useful when capturing fast-appearing targets (such as a jumping pet or a running child), as it can effectively reduce the number of failed shots caused by focusing delays.

In industrial automated production lines, cameras need to continuously focus and shoot high-speed moving workpieces, and focusing speed directly affects the efficiency of the production line. The collaborative operation of LiDAR and cameras enables the focusing system to synchronize with the movement of workpieces. The focusing adjustment time for each frame is controlled within an extremely short range, ensuring that the image of each workpiece is clearly distinguishable and meeting the real-time requirements of automated inspection.

Summary

LiDAR provides all-round improvements for camera focusing systems across five dimensions—environmental adaptability, dynamic focus tracking, precision control, intelligent decision-making, and speed optimization—by virtue of its core capabilities such as active ranging, high-precision perception, and real-time dynamic tracking. With the decreasing cost and maturing miniaturization technology of LiDAR, its integrated applications with cameras have expanded from professional fields like industry and security to consumer electronics (e.g., smartphones and home cameras). In the future, it will further drive the development of focusing technologies toward the direction of "perception-free, zero-latency, and high-precision", delivering superior experiences for various imaging scenarios.