Road User Detection in Videos

Successive frames of a video are highly redundant, and the most popular object detection methods do not take advantage of this fact. Using multiple consecutive frames can improve detection of small objects or difficult examples and can improve speed and detection consistency in a video sequence, for instance by interpolating features between frames. In this work, a novel approach is introduced to perform online video object detection using two consecutive frames of video sequences involving road users. Two new models, RetinaNet-Double and RetinaNet-Flow, are proposed, based respectively on the concatenation of a target frame with a preceding frame, and the concatenation of the optical flow with the target frame. The models are trained and evaluated on three public datasets. Experiments show that using a preceding frame improves performance over single frame detectors, but using explicit optical flow usually does not

Road User Detection in Videos

Successive frames of a video are highly redundant, and the most popular object detection methods do not take advantage of this fact. Using multiple consecutive frames can improve detection of small objects or difficult examples and can improve speed and detection consistency in a video sequence, for instance by interpolating features between frames. In this work, a novel approach is introduced to perform online video object detection using two consecutive frames of video sequences involving road users. Two new models, RetinaNet-Double and RetinaNet-Flow, are proposed, based respectively on the concatenation of a target frame with a preceding frame, and the concatenation of the optical flow with the target frame. The models are trained and evaluated on three public datasets. Experiments show that using a preceding frame improves performance over single frame detectors, but using explicit optical flow usually does not

RN-VID: A Feature Fusion Architecture for Video Object Detection

Consecutive frames in a video are highly redundant. Therefore, to perform the task of video object detection, executing single frame detectors on every frame without reusing any information is quite wasteful. It is with this idea in mind that we propose RN-VID (standing for RetinaNet-VIDeo), a novel approach to video object detection. Our contributions are twofold. First, we propose a new architecture that allows the usage of information from nearby frames to enhance feature maps. Second, we propose a novel module to merge feature maps of same dimensions using re-ordering of channels and 1 x 1 convolutions. We then demonstrate that RN-VID achieves better mean average precision (mAP) than corresponding single frame detectors with little additional cost during inference

Stringent Limits on the Polarized Submillimeter Emission from Protoplanetary Disks

We present arcsecond-resolution Submillimeter Array (SMA) polarimetric observations of the 880 um continuum emission from the protoplanetary disks around two nearby stars, HD 163296 and TW Hydrae. Although previous observations and theoretical work have suggested that a 2-3% polarization fraction should be common for the millimeter continuum emission from such disks, we detect no polarized continuum emission above a 3-sigma upper limit of 7 mJy in each arcsecond-scale beam, or <1% in integrated continuum emission. We compare the SMA upper limits with the predictions from the exploratory Cho & Lazarian (2007) model of polarized emission from T Tauri disks threaded by toroidal magnetic fields, and rule out their fiducial model at the ~10-sigma level. We explore some potential causes for this discrepancy, focusing on model parameters that describe the shape, magnetic field alignment, and size distribution of grains in the disk. We also investigate related effects like the magnetic field strength and geometry, scattering off of large grains, and the efficiency of grain alignment, including recent advances in grain alignment theory, which are not considered in the fiducial model. We discuss the impact each parameter would have on the data and determine that the suppression of polarized emission plausibly arises from rounding of large grains, reduced efficiency of grain alignment with the magnetic field, and/or some degree of magnetic field tangling (perhaps due to turbulence). A poloidal magnetic field geometry could also reduce the polarization signal, particularly for a face-on viewing geometry like the TW Hya disk. The data provided here offer the most stringent limits to date on the polarized millimeter-wavelength emission from disks around young stars.Comment: 15 pages, 6 figures, accepted for publication in Ap

Using BEAM Software to Simulate the Introduction of On-Demand, Automated, and Electric Shuttles for Last Mile Connectivity in Santa Clara County

Despite growing interest in low-speed automated shuttles, pilot deployments have only just begun in a few places in the U.S., and there is a lack of studies that estimate the impacts of a widespread deployment of automated shuttles designed to supplement existing transit networks. This project estimated the potential impacts of automated shuttles based on a deployment scenario generated for a sample geographic area: Santa Clara County, California. The project identified sample deployment markets within Santa Clara County using a GIS screening exercise; tested the mode share changes of an automated shuttle deployment scenario using BEAM, an open-source beta software developed at the Lawrence Berkeley National Laboratory to run traffic simulations with MATSim; elaborated the model outputs within the R environment; and then estimated the related impacts. The main findings have been that the BEAM software, despite still being in its beta version, was able to model a scenario with the automated shuttle service: this report illustrates the potential of the software and the lessons learned. Regarding transportation aspects, the model estimated automated shuttle use throughout the county, with a higher rate of use in the downtown San José area. The shuttles would be preferred mainly by people who had been using gasoline-powered ride hail vehicles for A-to-B trips or going to the bus stop, as well as walking trips and a few car trips directed to public transport stops. As a result, the shuttles contributed to a small decrease in emissions of air pollutants, provided a competitive solution for short trips, and increased the overall use of the public transport system. The shuttles also presented a solution for short night trips—mainly between midnight and 2 am—when there are not many options for moving between points A and B. The conclusion is that the automated shuttle service is a good solution in certain contexts and can increase public transit ridership overall

Observation of the topological Anderson insulator in disordered atomic wires

Topology and disorder have deep connections and a rich combined influence on quantum transport. In order to probe these connections, we synthesized one-dimensional chiral symmetric wires with controllable disorder via spectroscopic Hamiltonian engineering, based on the laser-driven coupling of discrete momentum states of ultracold atoms. We characterize the system's topology through measurement of the mean chiral displacement of the bulk density extracted from quench dynamics. We find evidence for the topological Anderson insulator phase, in which the band structure of an otherwise trivial wire is driven topological by the presence of added disorder. In addition, we observed the robustness of topological wires to weak disorder and measured the transition to a trivial phase in the presence of strong disorder. Atomic interactions in this quantum simulation platform will enable future realizations of strongly interacting topological fluids.Comment: 6 pages, 3 figures; 9 pages of supplementary material

Renormalization of composite operators

The blocked composite operators are defined in the one-component Euclidean scalar field theory, and shown to generate a linear transformation of the operators, the operator mixing. This transformation allows us to introduce the parallel transport of the operators along the RG trajectory. The connection on this one-dimensional manifold governs the scale evolution of the operator mixing. It is shown that the solution of the eigenvalue problem of the connection gives the various scaling regimes and the relevant operators there. The relation to perturbative renormalization is also discussed in the framework of the $\phi^3$ theory in dimension $d=6$.Comment: 24 pages, revtex (accepted by Phys. Rev. D), changes in introduction and summar

A supervised clustering approach for fMRI-based inference of brain states

We propose a method that combines signals from many brain regions observed in functional Magnetic Resonance Imaging (fMRI) to predict the subject's behavior during a scanning session. Such predictions suffer from the huge number of brain regions sampled on the voxel grid of standard fMRI data sets: the curse of dimensionality. Dimensionality reduction is thus needed, but it is often performed using a univariate feature selection procedure, that handles neither the spatial structure of the images, nor the multivariate nature of the signal. By introducing a hierarchical clustering of the brain volume that incorporates connectivity constraints, we reduce the span of the possible spatial configurations to a single tree of nested regions tailored to the signal. We then prune the tree in a supervised setting, hence the name supervised clustering, in order to extract a parcellation (division of the volume) such that parcel-based signal averages best predict the target information. Dimensionality reduction is thus achieved by feature agglomeration, and the constructed features now provide a multi-scale representation of the signal. Comparisons with reference methods on both simulated and real data show that our approach yields higher prediction accuracy than standard voxel-based approaches. Moreover, the method infers an explicit weighting of the regions involved in the regression or classification task

History, trauma and remembering in Kivu Ruhorahoza’s Grey Matter (2011)

In 1994, the genocide in Rwanda claimed at least 800,000 lives in just 100 days. More than 20 years on, the memory and trauma of the atrocities still permeate the Rwandan society. This article explores how some of these different manifestations of trauma (individual and collective, actual and inherited, real and imagined, that of survivors and perpetrators), and especially their relationship to the genocide as a historical event, shape the internationally recognized Rwandan feature film, Kivu Ruhorahoza’s Grey Matter (2011). Drawing on the scholarship on trauma, the article examines Grey Matter’s uniqueness within feature films on the topic and its ambition to tackle the impossibility of memory and objectivity vis-à-vis varied experiences of the genocide. It traces the connection between trauma and Grey Matter’s structure, which refuses to offer events a firm chronological placement, both within and beyond the narrative