Total Capture Time Research Articles

Compressive Non-Line-of-Sight Imaging with Deep Learning

In non-line-of-sight (NLOS) imaging, the spatial information of hidden targets is reconstructed from the time-of-light (TOF) of the multiple bounced signal photons. The need for NLOS imagers to perform extensive scanning in the transverse spatial dimensions constrains the imaging speed and reconstruction quality while limiting their applications on static scenes. Utilizing a photon TOF histogram with picosecond temporal resolution, we develop compressive non-line-of-sight imaging enabled by deep learning. Two-dimensional images ($32\ifmmode\times\else\texttimes\fi{}32$ pixels) of the NLOS targets can be reconstructed with superior reconstruction quality via a convolutional neural network (CNN), using significantly downscaled data ($8\ifmmode\times\else\texttimes\fi{}8$ scanning points) at a downsampling ratio of $6.25\mathrm{%}$ compared to the traditional methods. The CNN is end-to-end trained purely using simulated data but robust for image reconstruction with experiment data. Our results suggest that deep learning is effective for reducing the scanning points and total capture time towards scanningless NLOS imaging and videography.

Compressed sensing for active non-line-of-sight imaging.

Non-line-of-sight (NLOS) imaging techniques have the ability to look around corners, which is of growing interest for diverse applications. We explore compressed sensing in active NLOS imaging and show that compressed sensing can greatly reduce the required number of scanning points without the compromise of the imaging quality. Particularly, we perform the analysis for both confocal NLOS imaging and active occlusion-based periscopy. In experiment, we demonstrate confocal NLOS imaging with only 5 × 5 scanning points for reconstructing a three-dimensional hidden image which has 64 × 64 spatial resolution. The results show that compressed sensing can reduce the scanning points and the total capture time, while keeping the imaging quality. This will be desirable for high speed NLOS applications.

Deep-inverse correlography: towards real-time high-resolution non-line-of-sight imaging

Low signal-to-noise ratio (SNR) measurements, primarily due to the quartic attenuation of intensity with distance, are arguably the fundamental barrier to real-time, high-resolution, non-line-of-sight (NLoS) imaging at long standoffs. To better model, characterize, and exploit these low SNR measurements, we use spectral estimation theory to derive a noise model for NLoS correlography. We use this model to develop a speckle correlation-based technique for recovering occluded objects from indirect reflections. Then, using only synthetic data sampled from the proposed noise model, and without knowledge of the experimental scenes nor their geometry, we train a deep convolutional neural network to solve the noisy phase retrieval problem associated with correlography. We validate that the resulting deep-inverse correlography approach is exceptionally robust to noise, far exceeding the capabilities of existing NLoS systems both in terms of spatial resolution achieved and in terms of total capture time. We use the proposed technique to demonstrate NLoS imaging with 300 µm resolution at a 1 m standoff, using just two 1/8th s exposure-length images from a standard complementary metal oxide semiconductor detector.

Prediction of Opioid Analgesic Efficacy by Measurement of Pupillary Unrest.

Pupillary unrest under ambient light (PUAL) is the fluctuation in pupil diameter in time around a mean value. PUAL is augmented by light and diminished by administration of opioids. We hypothesized that, because pupillary unrest is a marker of opioid effect, low levels of PUAL may be associated with reduced opioid efficacy, as measured by changes in the numerical rating scale (NRS) pain scores of patients in the postanesthesia care unit (PACU). We used an infrared pupillometer to measure PUAL in patients recovering from ambulatory surgery at 2 different institutions. At both sites, PUAL was quantified using spectral analysis of the Fourier transform of pupil diameter versus time. We measured PUAL and pain scores before and after opioid administration. Protocols for total capture time and lighting conditions varied between the 2 sites. Correlations between PUAL and change in NRS scores were examined using significance testing of Pearson correlation coefficients. Correlations between change in PUAL and change in NRS scores were also examined. Patients were divided into high and low PUAL groups, and high and low response to opioid. A Fisher exact test was used to determine whether there was a significant association between PUAL and opioid response. For patients with pain in the PACU, low levels of pupillary unrest before opioid therapy were associated with minimal or no reduction in pain scores after opioid administration. We noted a significant correlation at both sites between PUAL and pain score reduction with opioids (r = 0.59, P = .0053, and r = 0.57, P = .022.) The Fisher exact test confirmed that patients with PUAL levels above the mean had a more beneficial analgesic effect from opioids than those with low PUAL levels (P = .018). We also noted that change in PUAL was significantly correlated with change in pain score at both sites (r = 0.56, P = .03 and r = 0.55, P = .01). We observe that the pretreatment magnitude of PUAL is correlated with the analgesic response to opioid therapy, and that patients who exhibit higher levels of PUAL change after opioid administration have a more beneficial analgesic effect from opioids. Larger studies with uniform measurement protocols are required to confirm these preliminary results.

Near‐Instant Capture of High‐Resolution Facial Geometry and Reflectance

AbstractWe present a near‐instant method for acquiring facial geometry and reflectance using a set of commodity DSLR cameras and flashes. Our setup consists of twenty‐four cameras and six flashes which are fired in rapid succession with subsets of the cameras. Each camera records only a single photograph and the total capture time is less than the 67ms blink reflex. The cameras and flashes are specially arranged to produce an even distribution of specular highlights on the face. We employ this set of acquired images to estimate diffuse color, specular intensity, specular exponent, and surface orientation at each point on the face. We further refine the facial base geometry obtained from multi‐view stereo using estimated diffuse and specular photometric information. This allows final submillimeter surface mesostructure detail to be obtained via shape‐from‐specularity. The final system uses commodity components and produces models suitable for authoring high‐quality digital human characters.

Hierarchically macro/mesoporous hybrid silica spheres for fast capture of heavy metal ions

Hybrid thiol-silica spheres constructed by interlacing arrays of submicrometer-sized blocks and large macropores were fabricated by a one-pot approach and were successfully used for the fast capture of heavy metal ions with a total capture time of less than 2min.

Noise reduction in high dynamic range imaging

A common method to create high dynamic range (HDR) images is to combine several different exposures of the same scene. In this approach, the use of higher ISO settings will reduce exposure times, and thereby the total capture time. This is advantageous in certain environments where it may help minimize ghosting artifacts. However, exposures taken at high sensitivity settings tend to be noisy, which is further amplified by the HDR creation algorithm. We present a robust and efficient technique to significantly reduce noise in an HDR image even when its constituent exposures are taken at very high ISO settings. The method does not introduce blur or other artifacts, and leverages the wealth of information available in a sequence of aligned exposures.

Studies on capture efficiencies of synchro-cyclotrons

In this paper it is shown that the capture time in a synchrocyclotron depends critically on the starting phase. The total capture time oer acceleration cycle has been derived from an integration over the starting phase interval 0°−60°. The fact that the phase oscillations are damped with increasing energy has been used to minimize the acceleration time. Intensities are estimated by means of the presented results on capture efficiencies and from available space-charge theories. A synchro-cyclotron of 600 MeV energy could be improved to deliver at least 60 μA of protons.