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Resolution improving method for a 3D environment modeling using omnidirectional image sensor

Recently, many applications in virtual reality and robotics require to create virtual environment from a real scene. A catadioptric omnidirectional image sensor composed of a convex mirror can observe a 360-degree field of view at once. It is useful for modeling a man-made environment such as a room, a corridor and a building, because the landmarks around the sensor can be taken and tracked by its large field of view. However, the angular resolution of the omnidirectional image is low owing to capturing the large field of view. Therefore, the resolution of texture patterns of each surface on the generated 3D scene model is not enough for monitoring details. To solve this problem, we propose a high-resolution scene texture generation method that combines an omnidirectional image sequence using image mosaic and super-resolution techniques.