Exploiting temporal information for 3D pose estimation

In this work, we address the problem of 3D human pose estimation from a sequence of 2D human poses. Although the recent success of deep networks has led many state-of-the-art methods for 3D pose estimation to train deep networks end-to-end to predict from images directly, the top-performing approaches have shown the effectiveness of dividing the task of 3D pose estimation into two steps: using a state-of-the-art 2D pose estimator to estimate the 2D pose from images and then mapping them into 3D space. They also showed that a low-dimensional representation like 2D locations of a set of joints can be discriminative enough to estimate 3D pose with high accuracy. However, estimation of 3D pose for individual frames leads to temporally incoherent estimates due to independent error in each frame causing jitter. Therefore, in this work we utilize the temporal information across a sequence of 2D joint locations to estimate a sequence of 3D poses. We designed a sequence-to-sequence network composed of layer-normalized LSTM units with shortcut connections connecting the input to the output on the decoder side and imposed temporal smoothness constraint during training. We found that the knowledge of temporal consistency improves the best reported result on Human3.6M dataset by approximately $12.2\%$ and helps our network to recover temporally consistent 3D poses over a sequence of images even when the 2D pose detector fails

Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image

We describe the first method to automatically estimate the 3D pose of the human body as well as its 3D shape from a single unconstrained image. We estimate a full 3D mesh and show that 2D joints alone carry a surprising amount of information about body shape. The problem is challenging because of the complexity of the human body, articulation, occlusion, clothing, lighting, and the inherent ambiguity in inferring 3D from 2D. To solve this, we first use a recently published CNN-based method, DeepCut, to predict (bottom-up) the 2D body joint locations. We then fit (top-down) a recently published statistical body shape model, called SMPL, to the 2D joints. We do so by minimizing an objective function that penalizes the error between the projected 3D model joints and detected 2D joints. Because SMPL captures correlations in human shape across the population, we are able to robustly fit it to very little data. We further leverage the 3D model to prevent solutions that cause interpenetration. We evaluate our method, SMPLify, on the Leeds Sports, HumanEva, and Human3.6M datasets, showing superior pose accuracy with respect to the state of the art.Comment: To appear in ECCV 201

Predictors of failed attendances in a multi-specialty outpatient centre using electronic databases.

BACKGROUND: Failure to keep outpatient medical appointments results in inefficiencies and costs. The objective of this study is to show the factors in an existing electronic database that affect failed appointments and to develop a predictive probability model to increase the effectiveness of interventions. METHODS: A retrospective study was conducted on outpatient clinic attendances at Tan Tock Seng Hospital, Singapore from 2000 to 2004. 22864 patients were randomly sampled for analysis. The outcome measure was failed outpatient appointments according to each patient's latest appointment. RESULTS: Failures comprised of 21% of all appointments and 39% when using the patients' latest appointment. Using odds ratios from the mutliple logistic regression analysis, age group (0.75 to 0.84 for groups above 40 years compared to below 20 years), race (1.48 for Malays, 1.61 for Indians compared to Chinese), days from scheduling to appointment (2.38 for more than 21 days compared to less than 7 days), previous failed appointments (1.79 for more than 60% failures and 4.38 for no previous appointments, compared with less than 20% failures), provision of cell phone number (0.10 for providing numbers compared to otherwise) and distance from hospital (1.14 for more than 14 km compared to less than 6 km) were significantly associated with failed appointments. The predicted probability model's diagnostic accuracy to predict failures is more than 80%. CONCLUSION: A few key variables have shown to adequately account for and predict failed appointments using existing electronic databases. These can be used to develop integrative technological solutions in the outpatient clinic

Supramolecular assemblies involving metal organic ring interactions: Heterometallic Cu(II)-Ln(III) two dimensional coordination polymers

Three isostructural two-dimensional coordination polymers of the general formula [Ln2(CuL)3(H2O)9]$5.5H2O, where Ln is La (1), Nd (2), and Gd (3), have been synthesized and isolated from aqueous solutions and their single-crystal structures determined by X-ray diffraction. The supramolecular interaction between the non-aromatic metallorings plays an important role in stabilizing the structure of these compounds. The thermal stability, reversible solvent uptake, electronic properties and magnetic studies of these compounds are also reported

Measurement of the cosmic microwave background polarization lensing power spectrum from two years of POLARBEAR data

We present a measurement of the gravitational lensing deflection power spectrum reconstructed with two seasons of cosmic microwave background polarization data from the POLARBEAR experiment. Observations were taken at 150 GHz from 2012 to 2014 and surveyed three patches of sky totaling 30 square degrees. We test the consistency of the lensing spectrum with a cold dark matter cosmology and reject the no-lensing hypothesis at a confidence of 10.9σ, including statistical and systematic uncertainties. We observe a value of AL = 1.33 ± 0.32 (statistical) ±0.02 (systematic) ±0.07 (foreground) using all polarization lensing estimators, which corresponds to a 24% accurate measurement of the lensing amplitude. Compared to the analysis of the first- year data, we have improved the breadth of both the suite of null tests and the error terms included in the estimation of systematic contamination

Internal delensing of cosmic microwave background polarization B-Modes with the POLARBEAR experiment

International audienceUsing only cosmic microwave background polarization data from the polarbear experiment, we measure B-mode polarization delensing on subdegree scales at more than 5σ significance. We achieve a 14% B-mode power variance reduction, the highest to date for internal delensing, and improve this result to 22% by applying for the first time an iterative maximum a posteriori delensing method. Our analysis demonstrates the capability of internal delensing as a means of improving constraints on inflationary models, paving the way for the optimal analysis of next-generation primordial B-mode experiments

Development and characterization of the readout system for POLARBEAR-2

POLARBEAR-2 is a next-generation receiver for precision measurements of the polarization of the cosmic microwave background (Cosmic Microwave Background (CMB)). Scheduled to deploy in early 2015, it will observe alongside the existing POLARBEAR-1 receiver, on a new telescope in the Simons Array on Cerro Toco in the Atacama desert of Chile. For increased sensitivity, it will feature a larger area focal plane, with a total of 7,588 polarization sensitive antenna-coupled Transition Edge Sensor (TES) bolometers, with a design sensitivity of 4.1 uKrt(s). The focal plane will be cooled to 250 milliKelvin, and the bolometers will be read-out with 40x frequency domain multiplexing, with 36 optical bolometers on a single SQUID amplifier, along with 2 dark bolometers and 2 calibration resistors. To increase the multiplexing factor from 8x for POLARBEAR-1 to 40x for POLARBEAR-2 requires additional bandwidth for SQUID readout and well-defined frequency channel spacing. Extending to these higher frequencies requires new components and design for the LC filters which define channel spacing. The LC filters are cold resonant circuits with an inductor and capacitor in series with each bolometer, and stray inductance in the wiring and equivalent series resistance from the capacitors can affect bolometer operation. We present results from characterizing these new readout components. Integration of the readout system is being done first on a small scale, to ensure that the readout system does not affect bolometer sensitivity or stability, and to validate the overall system before expansion into the full receiver. We present the status of readout integration, and the initial results and status of components for the full array.Comment: Presented at SPIE Astronomical Telescopes and Instrumentation 2014: Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy VII. Published in Proceedings of SPIE Volume 915

The bolometric focal plane array of the Polarbear CMB experiment

The Polarbear Cosmic Microwave Background (CMB) polarization experiment is currently observing from the Atacama Desert in Northern Chile. It will characterize the expected B-mode polarization due to gravitational lensing of the CMB, and search for the possible B-mode signature of inflationary gravitational waves. Its 250 mK focal plane detector array consists of 1,274 polarization-sensitive antenna-coupled bolometers, each with an associated lithographed band-defining filter. Each detector's planar antenna structure is coupled to the telescope's optical system through a contacting dielectric lenslet, an architecture unique in current CMB experiments. We present the initial characterization of this focal plane