Sewer pipelines play a crucial role in infrastructure, the economy, the environment, and public health. Failures in these systems are critical and cause severe damage. Regular inspection is necessary to provide maintenance and prevent failures. Traditional pipe inspection methods, which often require digging, are costly and risky. Having automatic and real-time pipe monitoring is essential. For this reason, advances in 3D modeling were developed integrating sensors, robots, and different algorithms. However, these methods often require expensive and complex hardware to be effective. Therefore, by implementing a 3D reconstruction algorithm, capable of integrating data from LiDAR and a single camera mounted on inspection robots, 3D modeling is achieved. Algorithm optimization through parallel processing drastically reduces time complexity, and GPU acceleration reduces the running time to achieve real-time performance. In this work, the parallel version of the algorithm has a speedup of 1.6 with respect to the serial version, achieving a running time of 5.23 s for a 20 m pipe. The algorithm’s implementation allows processing to be faster than data acquisition, which satisfies the requirement for real-time execution.