4,802 research outputs found
Motion magnification in coronal seismology
We introduce a new method for the investigation of low-amplitude transverse
oscillations of solar plasma non-uniformities, such as coronal loops,
individual strands in coronal arcades, jets, prominence fibrils, polar plumes,
and other contrast features, observed with imaging instruments. The method is
based on the two-dimensional dual tree complex wavelet transform
(DTWT). It allows us to magnify transverse, in the
plane-of-the-sky, quasi-periodic motions of contrast features in image
sequences. The tests performed on the artificial data cubes imitating
exponentially decaying, multi-periodic and frequency-modulated kink
oscillations of coronal loops showed the effectiveness, reliability and
robustness of this technique. The algorithm was found to give linear scaling of
the magnified amplitudes with the original amplitudes provided they are
sufficiently small. Also, the magnification is independent of the oscillation
period in a broad range of the periods. The application of this technique to
SDO/AIA EUV data cubes of a non-flaring active region allowed for the improved
detection of low-amplitude decay-less oscillations in the majority of loops.Comment: Accepted for publication in Solar Physic
Video Acceleration Magnification
The ability to amplify or reduce subtle image changes over time is useful in
contexts such as video editing, medical video analysis, product quality control
and sports. In these contexts there is often large motion present which
severely distorts current video amplification methods that magnify change
linearly. In this work we propose a method to cope with large motions while
still magnifying small changes. We make the following two observations: i)
large motions are linear on the temporal scale of the small changes; ii) small
changes deviate from this linearity. We ignore linear motion and propose to
magnify acceleration. Our method is pure Eulerian and does not require any
optical flow, temporal alignment or region annotations. We link temporal
second-order derivative filtering to spatial acceleration magnification. We
apply our method to moving objects where we show motion magnification and color
magnification. We provide quantitative as well as qualitative evidence for our
method while comparing to the state-of-the-art.Comment: Accepted paper at CVPR 2017. Project webpage:
http://acceleration-magnification.github.io
Exploiting Temporal Image Information in Minimally Invasive Surgery
Minimally invasive procedures rely on medical imaging instead of the surgeons direct vision. While preoperative images can be used for surgical planning and navigation, once the surgeon arrives at the target site real-time intraoperative imaging is needed. However, acquiring and interpreting these images can be challenging and much of the rich temporal information present in these images is not visible. The goal of this thesis is to improve image guidance for minimally invasive surgery in two main areas. First, by showing how high-quality ultrasound video can be obtained by integrating an ultrasound transducer directly into delivery devices for beating heart valve surgery. Secondly, by extracting hidden temporal information through video processing methods to help the surgeon localize important anatomical structures. Prototypes of delivery tools, with integrated ultrasound imaging, were developed for both transcatheter aortic valve implantation and mitral valve repair. These tools provided an on-site view that shows the tool-tissue interactions during valve repair. Additionally, augmented reality environments were used to add more anatomical context that aids in navigation and in interpreting the on-site video. Other procedures can be improved by extracting hidden temporal information from the intraoperative video. In ultrasound guided epidural injections, dural pulsation provides a cue in finding a clear trajectory to the epidural space. By processing the video using extended Kalman filtering, subtle pulsations were automatically detected and visualized in real-time. A statistical framework for analyzing periodicity was developed based on dynamic linear modelling. In addition to detecting dural pulsation in lumbar spine ultrasound, this approach was used to image tissue perfusion in natural video and generate ventilation maps from free-breathing magnetic resonance imaging. A second statistical method, based on spectral analysis of pixel intensity values, allowed blood flow to be detected directly from high-frequency B-mode ultrasound video. Finally, pulsatile cues in endoscopic video were enhanced through Eulerian video magnification to help localize critical vasculature. This approach shows particular promise in identifying the basilar artery in endoscopic third ventriculostomy and the prostatic artery in nerve-sparing prostatectomy. A real-time implementation was developed which processed full-resolution stereoscopic video on the da Vinci Surgical System
Quality Assurance of Lightweight Structures via Phase-based Motion Estimation
In recent years, lightweight structures have become mature and adopted in various applications. The importance of quality assurance cannot be overemphasized hence extensive research has been conducted to assess the quality of lightweight structures. This study investigates a novel process that exploits motion magnification to investigate the damage characteristics of lightweight mission-critical parts. The goal is to assure the structural integrity of 3D printed structures and composite structures by determining the inherent defects present in the part by exploiting their vibration characteristics. The minuscule vibration of the structure was recorded with the aid of a high-speed digital camera, and the motion was estimated by applying a phase-based algorithm. The spectral information was compared with the results obtained by a laser displacement sensor for validation. Then, the video-based results were used to perform damage identification by comparing the extracted information with that of a baseline. The resonance frequencies and the corresponding operational mode shapes of the test structure was obtained using the motion magnification algorithm by applying a bandpass filter around selected resonant frequencies. The resonance frequency and operational mode shape are quantified to compare the damaged structure with the baseline. The damage characteristics depending on the location and depth of damages were experimentally explored and numerically analyzed. Overall, this study provides an accurate, easily available and fast approach in structural health monitoring, utilizing video-based vibration analysis. It is envisioned that this study will provide a foundation for both commercial and non-commercial purposes exploiting the straightforward and low-cost implementation of video-based method
An Enhanced Indirect Video-Based Measurement Procedure for Dynamic Structural System Identification Applications
A video-based indirect sensing procedure for dynamic identification purposes is presented. To overcome major
limitations of video-based methods in real on-site measurements, a novel three step pre-modification, magnification, post-modification process is developed. This process includes revision of the initial input video record in
order to delete disturbing objects, utilizing a magnification method to filter the frequency content of the
monitored motion and using a revision step for elimination of noises generated during magnification process.
Finally, a set of digital signal and image processing analyses are performed on the modified video using virtual
visual sensor technology. Based on the results of this research, motion signals of the monitored object are
detected. The proposed approach has been used for identification of dynamic characteristics of two historic
masonry minarets in Istanbul. Results shows that the proposed procedure is able to assess the dynamic characteristics of the monitored structure with a high-level of accuracy
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