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Smart pixel imaging with computational-imaging arrays

Published in:
SPIE, Vol. 9070, Infrared Technology and Applications XL, 5 May 2014, 90703D.

Summary

Smart pixel imaging with computational-imaging arrays (SPICA) transfers image plane coding typically realized in the optical architecture to the digital domain of the focal plan array, thereby minimizing signal-to-noise losses associated with static filters or apertures and inherent diffraction concerns. MIT Lincoln Laboratory has been developing digital-pixel focal plane array (DFPA) devices for many years. In this work, we leverage legacy designs modified with new features to realize a computational imaging array (CIA) with advanced pixel-processing capabilities. We briefly review the use of DFPAs for on-chip background removal and image plane filtering. We focus on two digital readout integrated circuits (DROICS) as CIAs for two-dimensional (2D) transient target tracking and three-dimensional (3) transient target estimation using per-pixel coded-apertures or flutter shutters. This paper describes two DROICs -- a SWIR pixel-processing imager (SWIR-PPI) and a Visible CIA (VISCIA). SWIR-PPI is a DROIC with a 1 kHz global frame rate with a maximum per-pixel shuttering rate of 100 MHz, such that each pixel can be modulated by a time-varying, pseudo-random, and duo-binary signal (+1,-1,0). Combining per-pixel time-domain coding and processing enables 3D (x,y,T) target estimation with limited loss of spatial resolution. We evaluate structured and pseudo-random encoding strategies and employ linear inversion and non-linear inversion using total-variation minimization to estimate a 3D data cube from a single 2D temporally-encoded measurement. The VISCIA DROIC, while low-resolution, has a 6 kHz global frame rate and simultaneously encodes eight periodic or aperiodic transient target signatures at a maximum rate of 50 MHz using eight 8-bit counters. By transferring pixel-based image plane coding to the DROIC and utilizing sophisticated processing, our CIAs enable on-chip temporal super-resolution.
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Summary

Smart pixel imaging with computational-imaging arrays (SPICA) transfers image plane coding typically realized in the optical architecture to the digital domain of the focal plan array, thereby minimizing signal-to-noise losses associated with static filters or apertures and inherent diffraction concerns. MIT Lincoln Laboratory has been developing digital-pixel focal plane array...

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Exploiting morphological, grammatical, and semantic correlates for improved text difficulty assessment

Author:
Published in:
Proc. 9th Workshop on Innovative Use of NLP for Building Educational Applications, 26 June 2014, pp. 155-162.

Summary

We present a low-resource, language-independent system for text difficulty assessment. We replicate and improve upon a baseline by Shen et al. (2013) on the Interagency Language Roundtable (ILR) scale. Our work demonstrates that the addition of morphological, information theoretic, and language modeling features to a traditional readability baseline greatly benefits our performance. We use the Margin-Infused Relaxed Algorithm and Support Vector Machines for experiments on Arabic, Dari, English, and Pashto, and provide a detailed analysis of our results.
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Summary

We present a low-resource, language-independent system for text difficulty assessment. We replicate and improve upon a baseline by Shen et al. (2013) on the Interagency Language Roundtable (ILR) scale. Our work demonstrates that the addition of morphological, information theoretic, and language modeling features to a traditional readability baseline greatly benefits...

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Audio-visual identity grounding for enabling cross media search

Author:
Published in:
IEEE Computer Vision and Pattern Recognition Big Data Workshop, 23 June 2014.

Summary

Automatically searching for media clips in large heterogeneous datasets is an inherently difficult challenge, and nearly impossibly so when searching across distinct media types (e.g. finding audio clips that match an image). In this paper we introduce the exploitation of identity grounding for enabling this cross media search and exploration capability. Through the use of grounding we leverage one media channel (e.g. visual identity) as a noisy label for training a model in a different channel (e.g. audio speaker model). Finally, we demonstrate this search capability using images from the Labeled Faces in the Wild (LFW) dataset to query audio files that have been extracted from the YouTube Faces (YTF) dataset.
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Summary

Automatically searching for media clips in large heterogeneous datasets is an inherently difficult challenge, and nearly impossibly so when searching across distinct media types (e.g. finding audio clips that match an image). In this paper we introduce the exploitation of identity grounding for enabling this cross media search and exploration...

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New CCD imagers for adaptive optics wavefront sensors

Published in:
SPIE, Vol. 9148, Adaptive Optics Systems IV, 22 June 2014, 91485O.

Summary

We report on two recently developed charge-coupled devices (CCDs) for adaptive optics wavefront sensing, both designed to provide exceptional sensitivity (low noise and high quantum efficiency) in high-frame-rate low-latency readout applications. The first imager, the CCID75, is a back-illuminated 16-port 160x160 pixel CCD that has been demonstrated to operate at frame rates above 1,300 fps with noise of
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Summary

We report on two recently developed charge-coupled devices (CCDs) for adaptive optics wavefront sensing, both designed to provide exceptional sensitivity (low noise and high quantum efficiency) in high-frame-rate low-latency readout applications. The first imager, the CCID75, is a back-illuminated 16-port 160x160 pixel CCD that has been demonstrated to operate at...

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Active hyperspectral imaging using a quantum cascade laser (QCL) array and digital-pixel focal plane array (DFPA) camera

Summary

We demonstrate active hyperspectral imaging using a quantum-cascade laser (QCL) array as the illumination source and a digital-pixel focal-plane-array (DFPA) camera as the receiver. The multi-wavelength QCL array used in this work comprises 15 individually addressable QCLs in which the beams from all lasers are spatially overlapped using wavelength beam combining (WBC). The DFPA camera was configured to integrate the laser light relfected from the sample and to perform on-chip subtraction of the passive thermal background. A 27-frame hyperspectral image was acquired of a liquid contaminant on a diffuse gold surface at a range of 5 meters. The measured spectral reflectance closely matches the calculated reflectance. Furthermore, the high-speed capabilities of the system were demonstrated by capturing differential reflectance images of sand and KClO3 particles that were moving at speeds of up to 10 m/s.
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Summary

We demonstrate active hyperspectral imaging using a quantum-cascade laser (QCL) array as the illumination source and a digital-pixel focal-plane-array (DFPA) camera as the receiver. The multi-wavelength QCL array used in this work comprises 15 individually addressable QCLs in which the beams from all lasers are spatially overlapped using wavelength beam...

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Simultaneous dynamic pupil coding with on-chip coded aperture temporal imaging

Published in:
SRS 2014: Signal Recovery and Synthesis Conf., 13-17 June 2014.

Summary

We describe a new sensor that combines dynamic pupil coding with a digital readout integrated circuit (DROIC) capable of modulating a scene with a global or per-pixel time-varying, pseudo-random, and duo-binary signal (+1-1,0).
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Summary

We describe a new sensor that combines dynamic pupil coding with a digital readout integrated circuit (DROIC) capable of modulating a scene with a global or per-pixel time-varying, pseudo-random, and duo-binary signal (+1-1,0).

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Application of the Fornasini-Marchesini first model to data collected on a complex target model

Summary

This work describes the computation of scatterers that lay on the body of a real target which are depicted in radar images. A novelty of the approach is the target echoes collected by the radar are formulated into the first Fornasini-Marchesini (F-M) state space model to compute poles that give rise to the scatterer locations in the two-dimensional (2-D) space. Singular value decomposition carried out on the data provides state matrices that capture the dynamics of the target. Furthermore, eigenvalues computed from the state transition matrices provide range and cross-range locations of the scatterers that exhibit the target silhouette in 2-D space. The maximum likelihood function is formulated with the state matrices to obtain an iterative expression for the Fisher information matrix (FIM) from which posterior Cramer-Rao bounds associated with the various scatterers are derived. Effectiveness of the 2-D state-space technique is tested on static range data collected on a complex conical target model; its accuracy to extract target length is judged and compared with the physical measurements. Validity of the proposed 2-D state-space technique and the Cramer-Rao bounds are demonstrated through data collected on the target model.
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Summary

This work describes the computation of scatterers that lay on the body of a real target which are depicted in radar images. A novelty of the approach is the target echoes collected by the radar are formulated into the first Fornasini-Marchesini (F-M) state space model to compute poles that give...

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A new multiple choice comprehension test for MT

Published in:
Automatic and Manual Metrics for Operation Translation Evaluation Workshop, 9th Int. Conf. on Language Resources and Evaluation (LREC 2014), 26 May 2014.

Summary

We present results from a new machine translation comprehension test, similar to those developed in previous work (Jones et al., 2007). This test has documents in four conditions: (1) original English documents; (2) human translations of the documents into Arabic; conditions (3) and (4) are machine translations of the Arabic documents into English from two different MT systems. We created two forms of the test: Form A has the original English documents and output from the two Arabic-to-English MT systems. Form B has English, Arabic, and one of the MT system outputs. We administered the comprehension test to three subject types recruited in the greater Boston area: (1) native English speakers with no Arabic skills, (2) Arabic language learners, and (3) Native Arabic speakers who also have English language skills. There were 36 native English speakers, 13 Arabic learners, and 11 native Arabic speakers with English skills. Subjects needed an average of 3.8 hours to complete the test, which had 191 questions and 59 documents. Native English speakers with no Arabic skills saw Form A. Arabic learners and native Arabic speakers saw form B.
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Summary

We present results from a new machine translation comprehension test, similar to those developed in previous work (Jones et al., 2007). This test has documents in four conditions: (1) original English documents; (2) human translations of the documents into Arabic; conditions (3) and (4) are machine translations of the Arabic...

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Standardized ILR-based and task-based speech-to-speech MT evaluation

Published in:
Automatic and Manual Metrics for Operation Translation Evaluation Workshop, 9th Int. Conf. on Language Resources and Evaluation (LREC 2014), 26 May 2014.

Summary

This paper describes a new method for task-based speech-to-speech machine translation evaluation, in which tasks are defined and assessed according to independent published standards, both for the military tasks performed and for the foreign language skill levels used. We analyze task success rates and automatic MT evaluation scores (BLEU and METEOR) for 220 role-play dialogs. Each role-play team consisted of one native English-speaking soldier role player, one native Pashto-speaking local national role player, and one Pashto/English interpreter. The overall PASS score, averaged over all of the MT dialogs, was 44%. The average PASS rate for HT was 95%, which is important because a PASS requires that the role-players know the tasks. Without a high PASS rate in the HT condition, we could not be sure that the MT condition was not being unfairly penalized. We learned that success rates depended as much on task simplicity as it did upon the translation condition: 67% of simple, base-case scenarios were successfully completed using MT, whereas only 35% of contrasting scenarios with even minor obstacles received passing scores. We observed that MT had the greatest chance of success when the task was simple and the language complexity needs were low.
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Summary

This paper describes a new method for task-based speech-to-speech machine translation evaluation, in which tasks are defined and assessed according to independent published standards, both for the military tasks performed and for the foreign language skill levels used. We analyze task success rates and automatic MT evaluation scores (BLEU and...

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Wind information requirements for NextGen applications - phase 2 final report - framework refinement and application to four-dimensional trajectory based operations (4D-TBO) and interval management (IM)

Published in:
MIT Lincoln Laboratory Report ATC-418
Topic:

Summary

Accurate wind information is of fundamental importance to some of the critical future air traffic concepts under the FAA's Next Generation Air Transportation System (NextGen) initiative. Concepts involving time elements, such as Four-Dimensional Trajectory Based Operations (4D-TBO) and Interval Management (IM), are especially sensitive to wind information accuracy. There is a growing need to establish appropriate concepts of operation and target performance requirements accounting for wind information accuracy for these types of procedure, and meeting these needs is the purpose of this project. In the first phase of this work, a Wind Information Analysis Framework was developed to help explore the relationship of wind information to NextGen application performance. A refined version of the framework has been developed for the Phase 2 work that highlights the role stakeholders play in defining Air Traffic Control (ATC) scenarios, distinguishes wind scenarios into benign, moderate, severe, and extreme categories, and more clearly identifies what and how wind requirements recommendations are developed from the performance assessment trade-spaces. This report documents how this refined analysis framework has been used in Phase 2 of the work in terms of: -Refined wind information metrics and wind scenario selection process applicable to a broader range of NextGen applications, with particular focus on 4D-TBO and IM. -Expanded and refined studies of 4D-TBO applications with current Flight Management Systems (FMS) (with MITRE collaboration) to identify more accurate trade-spaces using operational FMS capabilities with higher-fidelity aircraft models. -Expansion of the 4D-TBO study using incremental enhancements possible in future FMSs (with Honeywell collaboration), specifically in the area of wind blending algorithms to quantify performance improvement potential from near-term avionics refinements. -Demonstrating the adaptability of the Wind Information Analysis Framework by using it to identify initial wind information needs for IM applications.
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Summary

Accurate wind information is of fundamental importance to some of the critical future air traffic concepts under the FAA's Next Generation Air Transportation System (NextGen) initiative. Concepts involving time elements, such as Four-Dimensional Trajectory Based Operations (4D-TBO) and Interval Management (IM), are especially sensitive to wind information accuracy. There is...

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