23,983 research outputs found
Encoding of arbitrary micrometric complex illumination patterns with reduced speckle
In nonlinear microscopy, phase-only spatial light modulators (SLMs) allow
achieving simultaneous two-photon excitation and fluorescence emission from specific regionof-interests (ROIs). However, as iterative Fourier transform algorithms (IFTAs) can only
approximate the illumination of selected ROIs, both image formation and/or signal acquisition
can be largely affected by the spatial irregularities of the illumination patterns and the speckle
noise. To overcome these limitations, we propose an alternative complex illumination method
(CIM) able to generate simultaneous excitation of large-area ROIs with full control over the
amplitude and phase of light and reduced speckle. As a proof-of-concept we experimentally
demonstrate single-photon and second harmonic generation (SHG) with structured
illumination over large-area ROIs
Tracking icebergs with time-lapse photography and sparse optical flow, LeConte Bay, Alaska, 2016â2017
We present a workflow to track icebergs in proglacial fjords using oblique time-lapse photos
and the Lucas-Kanade optical flow algorithm. We employ the workflow at LeConte Bay, Alaska, where we ran five time-lapse cameras between April 2016 and September 2017, capturing more than 400 000 photos at frame rates of 0.5â4.0 minâ1. Hourly to daily average velocity fields in map coordinates illustrate dynamic currents in the bay, with dominant downfjord velocities (exceeding 0.5 m sâ1 intermittently) and several eddies. Comparisons with simultaneous Acoustic Doppler Current Profiler (ADCP) measurements yield best agreement for the uppermost ADCP levels (⌠12 m and above), in line with prevalent small icebergs that trace near-surface currents. Tracking results from multiple cameras compare favorably, although cameras with lower frame rates (0.5 minâ1) tend to underestimate high flow speeds. Tests to determine requisite temporal and spatial image resolution confirm the importance of high image frame rates, while spatial resolution is of secondary importance. Application of our procedure to other fjords will be successful if iceberg concentrations are high enough and if the camera frame rates are sufficiently rapid (at least 1 minâ1 for conditions similar to LeConte Bay).This work was funded by the U.S. National Science Foundation (OPP-1503910, OPP-1504288, OPP-1504521 and OPP-1504191).Ye
Three-dimensional scanless holographic optogenetics with temporal focusing (3D-SHOT).
Optical methods capable of manipulating neural activity with cellular resolution and millisecond precision in three dimensions will accelerate the pace of neuroscience research. Existing approaches for targeting individual neurons, however, fall short of these requirements. Here we present a new multiphoton photo-excitation method, termed three-dimensional scanless holographic optogenetics with temporal focusing (3D-SHOT), which allows precise, simultaneous photo-activation of arbitrary sets of neurons anywhere within the addressable volume of a microscope. This technique uses point-cloud holography to place multiple copies of a temporally focused disc matching the dimensions of a neurons cell body. Experiments in cultured cells, brain slices, and in living mice demonstrate single-neuron spatial resolution even when optically targeting randomly distributed groups of neurons in 3D. This approach opens new avenues for mapping and manipulating neural circuits, allowing a real-time, cellular resolution interface to the brain
Astrometry with the Wide-Field InfraRed Space Telescope
The Wide-Field InfraRed Space Telescope (WFIRST) will be capable of
delivering precise astrometry for faint sources over the enormous field of view
of its main camera, the Wide-Field Imager (WFI). This unprecedented combination
will be transformative for the many scientific questions that require precise
positions, distances, and velocities of stars. We describe the expectations for
the astrometric precision of the WFIRST WFI in different scenarios, illustrate
how a broad range of science cases will see significant advances with such
data, and identify aspects of WFIRST's design where small adjustments could
greatly improve its power as an astrometric instrument.Comment: version accepted to JATI
Robust eye tracking based on multiple corneal reflections for clinical applications
Postprint (published version
Reflectance Intensity Assisted Automatic and Accurate Extrinsic Calibration of 3D LiDAR and Panoramic Camera Using a Printed Chessboard
This paper presents a novel method for fully automatic and convenient
extrinsic calibration of a 3D LiDAR and a panoramic camera with a normally
printed chessboard. The proposed method is based on the 3D corner estimation of
the chessboard from the sparse point cloud generated by one frame scan of the
LiDAR. To estimate the corners, we formulate a full-scale model of the
chessboard and fit it to the segmented 3D points of the chessboard. The model
is fitted by optimizing the cost function under constraints of correlation
between the reflectance intensity of laser and the color of the chessboard's
patterns. Powell's method is introduced for resolving the discontinuity problem
in optimization. The corners of the fitted model are considered as the 3D
corners of the chessboard. Once the corners of the chessboard in the 3D point
cloud are estimated, the extrinsic calibration of the two sensors is converted
to a 3D-2D matching problem. The corresponding 3D-2D points are used to
calculate the absolute pose of the two sensors with Unified Perspective-n-Point
(UPnP). Further, the calculated parameters are regarded as initial values and
are refined using the Levenberg-Marquardt method. The performance of the
proposed corner detection method from the 3D point cloud is evaluated using
simulations. The results of experiments, conducted on a Velodyne HDL-32e LiDAR
and a Ladybug3 camera under the proposed re-projection error metric,
qualitatively and quantitatively demonstrate the accuracy and stability of the
final extrinsic calibration parameters.Comment: 20 pages, submitted to the journal of Remote Sensin
Sensor node localisation using a stereo camera rig
In this paper, we use stereo vision processing techniques to
detect and localise sensors used for monitoring simulated
environmental events within an experimental sensor network testbed. Our sensor nodes communicate to the camera through patterns emitted by light emitting diodes (LEDs). Ultimately, we envisage the use of very low-cost, low-power,
compact microcontroller-based sensing nodes that employ
LED communication rather than power hungry RF to transmit data that is gathered via existing CCTV infrastructure.
To facilitate our research, we have constructed a controlled
environment where nodes and cameras can be deployed and
potentially hazardous chemical or physical plumes can be
introduced to simulate environmental pollution events in a
controlled manner. In this paper we show how 3D spatial
localisation of sensors becomes a straightforward task when
a stereo camera rig is used rather than a more usual 2D
CCTV camera
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