To address the problem of accurate measurement of relative pose of the target object in machine vision, this paper proposed a method, which applies a depth camera to acquire 3D point cloud data of target object, to achieve its relative pose perception. This method selected homonymous points based on a priori knowledge of spatial structure of the target object and applied a single binocular vision measurement system to obtain the 3D point cloud data of the target object while analyzing and processing the data to achieve homonymous point recognition. Furthermore, this method calculated the coordinate values of three homonymous points of the target object on the object coordinate system and the camera coordinate system, respectively, and solved the relative pose by using singular value decomposition (SVD). This method effectively solved the problem of 3D object pose perception and improved the efficiency of pose perception. The experimental data demonstrate that the relative error of six degrees of freedom measured by the proposed method is within ±0.5° and ±1 mm, which satisfies the application of machine vision pose perception in industrial production.