3D Object Reconstruction Using Full Pixel Matching

This paper proposes an approach to reconstruct 3D object from a sequence of 2D images using 2D Continuous Dynamic Programming algorithm (2DCDP) as full pixel matching technique. To avoid using both calibrated images and fundamental matrix in reconstructing 3D objects, the study uses the same approach with Factorization but aims to demonstrate the effectiveness in pixel matching of 2DCDP compared with other conventional methods such as Scale-Invariant Feature Transform (SIFT) or Kanade-Lucas-Tomasi tracker (KLT). The experiments in this study use relatively few uncalibrated images but still obtain accurate 3D objects, suggesting that our method is promising and superior to conventional methods.