CS 269 Class Project

Automatic 3D Reconstruction via Object Detection and 3D Transformable Model Matching

  • Class Instructor: Prof. Demetri Terzopoulos
  • The report of this project: [pdf]
  • Presentation in the class: [pdf]
  • Abstract:
  • In this project, we present a system that can automatically detect and 3D reconstruct the target objects. After the reconstruction, users can edit the image by scaling, translating, rotating and deleting the target objects. The system consists of three parts. The first part is the detection part. We use HOG (Histogram of Gradient) template matching for detection and adopt sliding window strategy with multiple scales and positions. We allow a small deformation of the HOG template. Non-maximum suppression is applied to remove duplicate detected windows. The second part is the 3D transformable model matching part. We will search for the optimal 3D models that match the edge maps of the detected target objects. The third part is the image editing part, the users can rotate, translate and scale multiple target objects detected in the image using simple operations of their mouse. The whole system will reduce the effort the user need to take, especially in the situation that the user need to 3D reconstruct near-duplicate objects in multiple images.