Visual stereo image generation from video data using phase correlation technique
We propose a new method for generating visual stereo images from the common two dimensional images without 3D reconstruction. The major novel contributions of this report are in two aspects. First, we address the detection of dominant motion presented in the given scenes, for doing so we borrow phase shift theorem and calculate the inverse Fourier transform of cross-power spectrum to find the maximum peak value whose position can be used to decide motion parameters. Secondly, unlike most of researchers study the stereo vision to recover 3D information for modeling and rendering, we address the visual stereo image generation without 3D reconstruction by applying the computed motion parameters to make decision of selecting two given images to form a stereo pair for left eye and right eye respectively. The proposed approaches can be employed for applications such as navigation in a virtual environment.
stereo image phase correlation monocular image dominant motion detection