Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Application of augmented reality and robotic technology in broadcasting: A survey

As an innovation technique, Augmented Reality (AR) has been gradually deployed in the broadcast, videography and cinematography industries. Virtual graphics generated by AR are dynamic and overlap on the surface of the environment so that the original appearance can be greatly enhanced in comparison with traditional broadcasting. In addition, AR enables broadcasters to interact with augmented virtual 3D models on a broadcasting scene in order to enhance the performance of broadcasting. Recently, advanced robotic technologies have been deployed in a camera shooting system to create a robotic cameraman so that the performance of AR broadcasting could be further improved, which is highlighted in the paper

D-touch: A Consumer-Grade Tangible Interface Module and Musical Applications

We define a class of tangible media applications that can be implemented on consumer-grade personal computers. These applications interpret user manipulation of physical objects in a restricted space and produce unlocalized outputs. We propose a generic approach to the implementation of such interfaces using flexible fiducial markers, which identify objects to a robust and fast video-processing algorithm, so they can be recognized and tracked in real time. We describe an implementation of the technology, then report two new, flexible music performance applications that demonstrate and validate it

Low vision assistance with mobile devices

Low vision affects many people, both young and old. Low vision conditions can range from near- and far-sightedness to conditions such as blind spots and tunnel vision. With the growing popularity of mobile devices such as smartphones, there is large opportunity for use of these multipurpose devices to provide low vision assistance. Furthermore, Google\u27s Android operating system provides a robust environment for applications in various fields, including low vision assistance. The objective of this thesis research is to develop a system for low vision assistance that displays important information at the preferred location of the user\u27s visual field. To that end, a first release of a prototype blind spot/tunnel vision assistance system was created and demonstrated on an Android smartphone. Various algorithms for face detection and face tracking were implemented on the Android platform and their performance was assessed with regards to metrics such as throughput and battery usage. Specifically, Viola-Jones, Support Vector Machines, and a color-based method from Pai et al were used for face detection. Template matching, CAMShift, and Lucas-Kanade methods were used for face tracking. It was found that face detection and tracking could be successfully executed within acceptable bounds of time and battery usage, and in some cases performed faster than it would take a comparable cloud-based system for offloading algorithm usage to complete execution