@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}
}
@conference {Tascini1994838,
	title = {Image sequence recognition},
	booktitle = {Proceedings of SPIE - The International Society for Optical Engineering},
	volume = {2308},
	number = {p 2},
	year = {1994},
	note = {cited By 1},
	pages = {838-847},
	abstract = {Image sequence recognition is a problem that occurs in computer vision and particularly in mobile robot vision. The feature based method has been selected to solve this problem. The method first extracts the features as corners, points of curvature, lines etc. Then the correspondence of these features is established between two successive frames, and finally motion parameters and object structure from correspondences are computed. Test results demonstrating the method are included.},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-0028735739\&partnerID=40\&md5=2752672a7fe70d15fb9df66474f82faf},
	author = {Guido Tascini and Primo Zingaretti}
}
