Selective visual odometry for accurate AUV localization

In this paper we present a stereo visual odometry system developed for autonomous underwater vehicle localization tasks. The main idea is to make use of only highly reliable data in the estimation process, employing a robust keypoint tracking approach and an effective keyframe selection strategy, so that camera movements are estimated with high accuracy even for long paths. Furthermore, in order to limit the drift error, camera pose estimation is referred to the last keyframe, selected by analyzing the feature temporal flow. The proposed system was tested on the KITTI evaluation framework and on the New Tsukuba stereo dataset to assess its effectiveness on long tracks and different illumination conditions. Results of a live archaeological campaign in the Mediterranean Sea, on an AUV equipped with a stereo camera pair, show that our solution can effectively work in underwater environments

Restoration and enhancement of historical stereo photos

Restoration of digital visual media acquired from repositories of historical photographic and cinematographic material is of key importance for the preservation, study and transmission of the legacy of past cultures to the coming generations. In this paper, a fully automatic approach to the digital restoration of historical stereo photographs is proposed, referred to as Stacked Median Restoration plus (SMR+). The approach exploits the content redundancy in stereo pairs for detecting and fixing scratches, dust, dirt spots and many other defects in the original images, as well as improving contrast and illumination. This is done by estimating the optical flow between the images, and using it to register one view onto the other both geometrically and photometrically. Restoration is then accomplished in three steps: (1) image fusion according to the stacked median operator, (2) low-resolution detail enhancement by guided supersampling, and (3) iterative visual consistency checking and refinement. Each step implements an original algorithm specifically designed for this work. The restored image is fully consistent with the original content, thus improving over the methods based on image hallucination. Comparative results on three different datasets of historical stereograms show the effectiveness of the proposed approach, and its superiority over single-image denoising and super-resolution methods. Results also show that the performance of the state-of-the-art single-image deep restoration network Bringing Old Photo Back to Life (BOPBtL) can be strongly improved when the input image is pre-processed by SMR+

Fast adaptive frame preprocessing for 3D reconstruction

This paper presents a new online preprocessing strategy to detect and discard ongoing bad frames in video sequences. These include frames where an accurate localization between corresponding points is difficult, such as for blurred frames, or which do not provide relevant information with respect to the previous frames in terms of texture, image contrast and non-flat areas. Unlike keyframe selectors and deblurring methods, the proposed approach is a fast preprocessing working on a simple gradient statistic, that does not require to compute complex time-consuming image processing, such as the computation of image feature keypoints, previous poses and 3D structure, or to know a priori the input sequence. The presented method provides a fast and useful frame pre-analysis which can be used to improve further image analysis tasks, including also the keyframe selection or the blur detection, or to directly filter the video sequence as shown in the paper, improving the final 3D reconstruction by discarding noisy frames and decreasing the final computation time by removing some redundant frames. This scheme is adaptive, fast and works at runtime by exploiting the image gradient statistic of the last few frames of the video sequence. Experimental results show that the proposed frame selection strategy is robust and improves the final 3D reconstruction both in terms of number of obtained 3D points and reprojection error, also reducing the computational time

Accurate keyframe selection and keypoint tracking for robust visual odometry

This paper presents a novel stereo visual odometry (VO) framework based on structure from motion, where a robust keypoint tracking and matching is combined with an effective keyframe selection strategy. In order to track and find correct feature correspondences a robust loop chain matching scheme on two consecutive stereo pairs is introduced. Keyframe selection is based on the proportion of features with high temporal disparity. This criterion relies on the observation that the error in the pose estimation propagates from the uncertainty of 3D points—higher for distant points, that have low 2D motion. Comparative results based on three VO datasets show that the proposed solution is remarkably effective and robust even for very long path lengths

A vision-based fully automated approach to robust image cropping detection

The definition of valid and robust methodologies for assessing the authenticity of digital information is nowadays critical to contrast social manipulation through the media. A key research topic in multimedia forensics is the development of methods for detecting tampered content in large image collections without any human intervention. This paper introduces AMARCORD (Automatic Manhattan-scene AsymmetRically CrOpped imageRy Detector), a fully automated detector for exposing evidences of asymmetrical image cropping on Manhattan-World scenes. The proposed solution estimates and exploits the camera principal point, i.e., a physical feature extracted directly from the image content that is quite insensitive to image processing operations, such as compression and resizing, typical of social media platforms. Robust computer vision techniques are employed throughout, so as to cope with large sources of noise in the data and improve detection performance. The method leverages a novel metric based on robust statistics, and is also capable to decide autonomously whether the image at hand is tractable or not. The results of an extensive experimental evaluation covering several cropping scenarios demonstrate the effectiveness and robustness of our approac

Robotic treatment of colorectal endometriosis: technique, feasibility and short-term results

background: Deep infiltrating endometriosis (DIE) is a complex disease that impairs the quality of life and the fertility of women. Since a medical approach is often insufficient, a minimally invasive approach is considered the gold standard for complete disease excision. Roboticassisted surgery is a revolutionary approach, with several advantages compared with traditional laparoscopic surgery. methods: From March 2010 to May 2011, we performed 22 consecutive robotic-assisted complete laparoscopic excisions of DIE endometriosis with colorectal involvement. All clinical data were collected by our team and all patients were interviewed preoperatively and 3 and 6 months post-operatively and yearly thereafter regarding endometriosis-related symptoms. Dysmenorrhoea, dyschezia, dyspareunia and dysuria were evaluated with a 10-point analog rating scale. results: There were 12 patients, with a median larger endometriotic nodule of 35 mm, who underwent segmental resection, and 10 patients, with a median larger endometriotic nodule of 30 mm, who underwent complete nodule debulking by colorectal wall-shaving technique. No laparotomic conversions were performed, nor was any blood transfusion necessary. No intra-operative complications were observed and, in particular, there were no inadvertent rectal perforations in any of the cases treated by the shaving technique. None of the patients had ileostomy or colostomy. No major post-operative complications were observed, except one small bowel occlusion 14 days post-surgery that was resolved in 3 days with medical treatment. Post-operatively, a statistically significant improvement of patient symptoms was shown for all the investigated parameters. conclusions: To our knowledge, this is the first study reporting the feasibility and short-term results and complications of laparoscopic robotic-assisted treatment of DIE with colorectal involvement.We demonstrate that this approach is feasible and safe, without conversion to laparotomy

ATLAS and CMS applications on the WorldGrid testbed

WorldGrid is an intercontinental testbed spanning Europe and the US integrating architecturally different Grid implementations based on the Globus toolkit. It has been developed in the context of the DataTAG and iVDGL projects, and successfully demonstrated during the WorldGrid demos at IST2002 (Copenhagen) and SC2002 (Baltimore). Two HEP experiments, ATLAS and CMS, successful exploited the WorldGrid testbed for executing jobs simulating the response of their detectors to physics eve nts produced by real collisions expected at the LHC accelerator starting from 2007. This data intensive activity has been run since many years on local dedicated computing farms consisting of hundreds of nodes and Terabytes of disk and tape storage. Within the WorldGrid testbed, for the first time HEP simulation jobs were submitted and run indifferently on US and European resources, despite of their underlying different Grid implementations, and produced data which could be retrieved and further analysed on the submitting machine, or simply stored on the remote resources and registered on a Replica Catalogue which made them available to the Grid for further processing. In this contribution we describe the job submission from Europe for both ATLAS and CMS applications, performed through the GENIUS portal operating on top of an EDG User Interface submitting to an EDG Resource Broker, pointing out the chosen interoperability solutions which made US and European resources equivalent from the applications point of view, the data management in the WorldGrid environment, and the CMS specific production tools which were interfaced to the GENIUS portal.Comment: Poster paper from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 10 pages, PDF. PSN TUCP004; added credit to funding agenc

Fertility sparing treatment for bilateral borderline ovarian tumor. A case report and management strategy explication

A bilateral adnexal mass with suspected carcinosis could be a challenging experience for the gynecologist especially in fertile age and in patients with a desire for pregnancy. A 26-year-old patient who came to the outpatient clinical observation for bilateral, multilocular pelvic masses, with more than 4 papillary structures, color score 2, hypomobile compared to the uterus and rectum, respectively of 65 and 68mm in maximum diameter, free liquid in the abdomen and suspected for ovarian neoplasm. Positive tumor markers and a strong desire of a Fertility Sparing Treatment (FST). A 2-steps surgical approach managed to perform a diagnosis of bilateral ovarian borderline tumor with implants and a fertility sparing surgery. Harvesting and cryopreserving oocytes prior to the cytoreductive intervention was successfully performed

Peritoneal carcinosis of ovarian origin

Epithelial ovarian cancer (EOC) is the second most common genital malignancy in women and is the most lethal gynecological malignancy, with an estimated five-year survival rate of 39%. Despite efforts to develop an effective ovarian cancer screening method, 60% of patients still present with advanced disease. Comprehensive management using surgical cytoreduction to decrease the tumor load to a minimum, and intraperitoneal chemotherapy to eliminate microscopic disease on peritoneal surface, has the potential to greatly improve quality of life and to have an impact on survival in ovarian cancer patients. Despite achieving clinical remission after completion of initial treatment, most patients (60%) with advanced EOC will ultimately develop recurrent disease or show drug resistance; the eventual rate of curability is less than 30%. Given the poor outcome of women with advanced EOC, it is imperative to continue to explore novel therapies.