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

LABORATORY SIMULATION OF TURBULENT-LIKE FLOWS

Most turbulence studies up to the present are based on statistical modeling, however, the spatio-temporal flow structure of the turbulence is still largely unexplored. Tur- bulence has been established to have a multi-scale instantaneous streamline structure which influences the energy spectrum and other properties such as dissipation and mixing. In an attempt to further understand the fundamental nature of turbulence and its consequences for efficient mixing, a new class of flows, so called “turbulent-like”, is in- troduced and its spatio-temporal structure of the flows characterised. These flows are generated in the laboratory using a shallow layer of brine and controlled by multi-scale electromagnetic forces resulting from a combination of electric current and a magnetic field created by a fractal permanent magnet distribution. These flows are laminar, yet turbulent-like, in that they have multi-scale streamline topology in the shape of “cat’s eyes” within “cat’s eyes” (or 8’s within 8’s) similar to the known schematic streamline structure of two-dimensional turbulence. Unsteadiness is introduced to the flows by means of time-dependent electrical current. Particle Tracking Velocimetry (PTV) measurements are performed. The technique developed provides highly resolved Eulerian velocity fields in space and time. The analysis focuses on the impact of the forcing frequency, mean intensity and amplitude on various Eulerian and Lagrangian properties of the flows e.g. energy spectrum and fluid element dispersion statistics. Other statistics such as the integral length and time scales are also extracted to characterise the unsteady multi-scale flows. The research outcome provides the analysis of laboratory generated unsteady multi- scale flows which are a tool for the controlled study of complex flow properties related to turbulence and mixing with potential applications as efficient mixers as well as in geophysical, environmental and industrial fields

Speech rhythms and multiplexed oscillatory sensory coding in the human brain

Cortical oscillations are likely candidates for segmentation and coding of continuous speech. Here, we monitored continuous speech processing with magnetoencephalography (MEG) to unravel the principles of speech segmentation and coding. We demonstrate that speech entrains the phase of low-frequency (delta, theta) and the amplitude of high-frequency (gamma) oscillations in the auditory cortex. Phase entrainment is stronger in the right and amplitude entrainment is stronger in the left auditory cortex. Furthermore, edges in the speech envelope phase reset auditory cortex oscillations thereby enhancing their entrainment to speech. This mechanism adapts to the changing physical features of the speech envelope and enables efficient, stimulus-specific speech sampling. Finally, we show that within the auditory cortex, coupling between delta, theta, and gamma oscillations increases following speech edges. Importantly, all couplings (i.e., brain-speech and also within the cortex) attenuate for backward-presented speech, suggesting top-down control. We conclude that segmentation and coding of speech relies on a nested hierarchy of entrained cortical oscillations

Visualization and Correction of Automated Segmentation, Tracking and Lineaging from 5-D Stem Cell Image Sequences

Results: We present an application that enables the quantitative analysis of multichannel 5-D (x, y, z, t, channel) and large montage confocal fluorescence microscopy images. The image sequences show stem cells together with blood vessels, enabling quantification of the dynamic behaviors of stem cells in relation to their vascular niche, with applications in developmental and cancer biology. Our application automatically segments, tracks, and lineages the image sequence data and then allows the user to view and edit the results of automated algorithms in a stereoscopic 3-D window while simultaneously viewing the stem cell lineage tree in a 2-D window. Using the GPU to store and render the image sequence data enables a hybrid computational approach. An inference-based approach utilizing user-provided edits to automatically correct related mistakes executes interactively on the system CPU while the GPU handles 3-D visualization tasks. Conclusions: By exploiting commodity computer gaming hardware, we have developed an application that can be run in the laboratory to facilitate rapid iteration through biological experiments. There is a pressing need for visualization and analysis tools for 5-D live cell image data. We combine accurate unsupervised processes with an intuitive visualization of the results. Our validation interface allows for each data set to be corrected to 100% accuracy, ensuring that downstream data analysis is accurate and verifiable. Our tool is the first to combine all of these aspects, leveraging the synergies obtained by utilizing validation information from stereo visualization to improve the low level image processing tasks.Comment: BioVis 2014 conferenc