@article {Zingaretti1998257,
	title = {Robust real-time detection of an underwater pipeline},
	journal = {Engineering Applications of Artificial Intelligence},
	volume = {11},
	number = {2},
	year = {1998},
	note = {cited By 14},
	pages = {257-268},
	abstract = {Currently, the methods of inspection of underwater structures employ remotely operated vehicles, guided from a support vessel by human operators. The risk of losing concentration calls for the development of an intelligent vision, guidance and control system to support the human activity. The paper presents a robust system for the detection and the real-time tracking of submarine pipelines. An active vision system is proposed to predict changes in the scene, and to direct computational resources to confirm expectations by adapting the processing mode dynamically. The system originates from an image-processing algorithm that was previously developed by the authors to recognise the pipeline in the image plane. The accuracy of this algorithm has been enhanced by exploiting the temporal context in the image sequence. The disturbances on acquired images caused by motion are partially removed by a Kalman filter. The filter proves advantageous in supporting the guidance and control of the ROV, and in making the image-processing module itself more robust. Sequences of underwater images, acquired at a constant sampling frequency from T.V. cameras, are used together with synchronised navigation data to demonstrate the effectiveness of the system. {\textcopyright} 1998 Elsevier Science Ltd. All rights reserved.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0032041493\&partnerID=40\&md5=188347e23a7078459b6de61720f8fff2},
	author = {Primo Zingaretti and S.M. Zanoli}
}
@conference {Zanoli199856,
	title = {Underwater imaging system to support ROV guidance},
	booktitle = {Oceans Conference Record (IEEE)},
	volume = {1},
	year = {1998},
	note = {cited By 1},
	pages = {56-60},
	abstract = {An underwater active vision system is proposed to support ROV guidance. The system exploits the temporal context in the image sequence to improve the precision in the computation of the pipeline contours, by adapting the processing mode dynamically. Disturbances of motion effect on acquired images are also partially removed by cascading a Kalman filter to an image processing module.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0032255064\&partnerID=40\&md5=ea30ad86202dc8ac07f8bdb5f8090de5},
	author = {S.M. Zanoli and Primo Zingaretti}
}
@conference {Conte19961213,
	title = {Automatic analysis of visual data in submarine pipeline inspection},
	booktitle = {Oceans Conference Record (IEEE)},
	volume = {3},
	year = {1996},
	note = {cited By 8},
	pages = {1213-1219},
	abstract = {An automatic system for analysis and interpretation of visual data from submarine pipeline inspection operates using images collected by cameras mounted on an unmanned Remotely Operated Vehicle (ROV) that moves along the pipeline. The system supports the operator in navigating the ROV and in detecting structural elements of the pipeline such as anodes, gravel heaps and reference bands. The system employs a feature based technique for recognizing the pipeline{\textquoteright}s profile and for detecting the structural elements. Information gathered by analyzing and interpreting the visual data can be used for automatic guidance and inspection by integrating the system into a larger architecture.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0030385353\&partnerID=40\&md5=d5723a92ebcff100f3868adc25135935},
	author = {Conte, G. and S.M. Zanoli and Perdon, A.M. and Guido Tascini and Primo Zingaretti}
}
@conference {Zingaretti1996129,
	title = {Imaging approach to real-time tracking of submarine pipeline},
	booktitle = {Proceedings of SPIE - The International Society for Optical Engineering},
	volume = {2661},
	year = {1996},
	note = {cited By 10},
	pages = {129-137},
	abstract = {The work presents a real-time underwater imaging system for identification and tracking of a submarine pipeline on a sequence of recorded images. The main novelty of this work relies on adopting an automatic approach that is entirely based on the analysis and interpretation of visual data, in spite of the various limitations upon the ability to image underwater objects. The analysis of the data is performed starting from image processing operations (like filtering, profile analysis, feature enhancement) implemented on a dedicated board. Then, the system employs an efficient dynamic process for recognizing the two contours of the pipeline. In each frame the system is able to determine the equations of the two straight lines corresponding to the pipeline contours. The system reaches satisfactory performances in real time operation: up to eight frames per second on a Pentium based PC. The results of this work are somewhat more meaningful as the input images were acquired by three cameras, mounted on a remotely operated vehicle travelling at one nautical mile an hour, without any attention either to illumination conditions or stability of cameras. This work is originated from the interest of Snamprogetti in enhancing the level of automation in submarine pipeline inspection.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0029754848\&partnerID=40\&md5=65001780f0cb94776ceeb1da3a6eec40},
	author = {Primo Zingaretti and Guido Tascini and Paolo Puliti and S.M. Zanoli}
}
