This technology calculates the position and orientation of a moving object by applying just two feature points extracted from a 2D camera image and their corresponding 3D information into a perspective projection matrix equation. It uses trigonometric synthesis to compute rotation (sinθ, cosθ) and translation (tx, ty) data at high speeds.
Conventional visual odometry technologies require a large number of image points to ensure accuracy, leading to high computational loads and limitations in real-time processing due to iterative optimization. They also rely heavily on expensive IMU or GPS/INS sensors, resulting in low cost-efficiency.
This technology defines a perspective projection matrix equation using only two image points and derives rotation and translation data using internal parameters (focal length, principal point). In particular, it significantly reduces computational complexity by synthesizing expressions containing sinθ and cosθ into a single trigonometric function.
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