Abstract: A method for generating a virtual scene comprising one or more 3D objects is provided. The method includes creating a 3D model of a real world 3D scene, capturing an image of the real world 3D scene by a physical camera to obtain a captured image, creating a digital camera model of the physical camera, rendering a virtual 3D scene comprising virtual 3D objects based on the digital camera model using physical-based rendering software to obtain a virtual image, and minimizing dissimilarity norm between the captured image and the virtual image to optimize positions and surface parameters of the virtual 3D objects in the virtual 3D scene.

Abstract: A motion estimation method for video data including frames and an apparatus therefor are provided. The motion estimation method includes determining whether a current frame unit for which motion estimation is to be performed corresponds to a double block, when the current frame unit corresponds to a double block, acquiring a candidate vector set corresponding to a first single block included in the double block, as a candidate vector set of the double block, individually calculating a confidence function value of each candidate vector included in the candidate vector set of the double block, for the first single block and a second single block included in the double block, and acquiring an estimated motion vector of the first single block and an estimated motion vector of the second single block, based on the calculated confidence function value of each candidate vector.

Abstract: A motion estimation method for video data including frames and an apparatus therefor are provided. The motion estimation method includes determining whether a current frame unit for which motion estimation is to be performed corresponds to a double block, when the current frame unit corresponds to a double block, acquiring a candidate vector set corresponding to a first single block included in the double block, as a candidate vector set of the double block, individually calculating a confidence function value of each candidate vector included in the candidate vector set of the double block, for the first single block and a second single block included in the double block, and acquiring an estimated motion vector of the first single block and an estimated motion vector of the second single block, based on the calculated confidence function value of each candidate vector.