目的 深度信息的获取是3维重建、虚拟现实等应用的关键技术，基于单目视觉的深度信息获取是非接触式3维测量技术中成本最低、也是技术难度最大的手段。传统的单目方法多基于线性透视、纹理梯度、运动视差、聚焦散焦等深度线索来对深度信息进行求取，计算量大，对相机精度要求高，应用场景受限，本文基于固定光强的点光源在场景中的移动所带来的物体表面亮度的变化，提出一种简单快捷的单目深度提取方法。方法 首先根据体表面反射模型，得到光源照射下的物体表面的辐亮度，然后结合光度立体学推导物体表面辐亮度与摄像机图像亮度之间的关系，在得到此关系式后，设计实验，依据点光源移动所带来的图像亮度的变化对深度信息进行求解。结果 该算法在简单场景和一些日常场景下均取得了较好的恢复效果，深度估计值与实际深度值之间的误差小于10%。结论 本文方法通过光源移动带来的图像亮度变化估计深度信息，避免了复杂的相机标定过程，计算复杂度小，是一种全新的场景深度信息获取方法。

Objective The development of machine vision field has made the use of visual methods to solve the problem of deep extraction a major topic in computer vision research. The scene image acquired by the monocular vision system is the projection of the 3D space in the 2D plane. The depth information is lost during this transformation. In turn, the process of extracting depth from 2D images involves the acquisition of monocular depth information. The acquisition of depth information based on monocular vision is the least costly and the most difficult means of non-contact 3D measurement technology. For a long time, the basic method is to analyze the surface brightness of the object under different light sources by use of the brightness equation to solve the surface normal and the 3D reconstruction of the surface of the object. Contrary to the proposed method, photometric techniques typically require multiple light sources, which are generally limited to a wide range of scenarios. The use of photometric 3D technology for 3D reconstruction of the surface of a single object to restore the effect is accurate. Thus, most existing photometric stereoscopic techniques assume that incident light is parallel to light and that light intensity does not change with distance to simplify the calculation process of the surface normal. To achieve this condition, the actual application must be light intensity, distance light source, or a large area of the array of light sources; such algorithm is used in the light source near the point of light (i.e., the light intensity) to meet the distance of the square inverse decay (i.e., in line with the actual situation) and achieve low cost. The extraction of depth information is the key technology of 3D reconstruction and virtual reality. Traditional monocular methods are computationally large that the application scenario is limited. Monocular information should be used to find a convenient way for quickly extracting the depth of a scene. Method In this study, we integrate photometric 3D, imaging principles, computer vision, and many other technologies for analysis. The radiance of surface of object illuminated by light source is obtained using the body surface reflection model, and the relation between the radiance of surface of object and the brightness of camera image is deduced using photometric stereo theory. The relationship between depth and change is found on the basis of the change in the brightness of image. The algorithm based on the said relationship is designed to obtain depth information. Result The algorithm is applied on various experimental scenarios. First, the depth value is estimated for the ladder-like object in the relatively simple scene. The actual distance is accurately measured by the scale, and the value is obtained after 2 decimal places. Then, the algorithm is used to calculate the depth value, which is after 4 decimal places, under the experimental conditions with a maximum total error of 8.6%. Results show that the maximum error of the experiment is less than 9%. The experimental conditions can be improved on the basis of the overall experimental results to achieve the desired requirements of the algorithm. Experimental results show that the proposed algorithm achieves good recovery in simple scenes and other daily scenes and that the accuracy of depth values is over 90%. Conclusion In this study, depth information is estimated by the image intensity change caused by the movement of light source, thereby avoiding the complicated camera calibration process. The algorithm presents a low computational complexity and is a new method for obtaining depth information. Meanings This study provides a new idea for acquiring monocular depth information based on image brightness cues. The method is based on the analysis of the relationship between surface radiance and image brightness and uses the change in light intensity of the point light source in the process of moving to obtain the scene depth value. The method requires only three pictures for processing, has simple hardware requirements and small calculation complexity, and does not need significant edge of scene and other geometric information. However, only the preliminary principle and performance verification of the proposed depth extraction method are presented herein. In the future work, the proposed method will be improved and optimized by analyzing non-ideal light sources in the case of light reflection of object and using mixed surface reflection models to fit the surface of the non-diffused reflector.