Search Tracker: Human-derived object tracking in-the-wild through large-scale search and retrieval

Humans use context and scene knowledge to easily localize moving objects in conditions of complex illumination changes, scene clutter and occlusions. In this paper, we present a method to leverage human knowledge in the form of annotated video libraries in a novel search and retrieval based setting to track objects in unseen video sequences. For every video sequence, a document that represents motion information is generated. Documents of the unseen video are queried against the library at multiple scales to find videos with similar motion characteristics. This provides us with coarse localization of objects in the unseen video. We further adapt these retrieved object locations to the new video using an efficient warping scheme. The proposed method is validated on in-the-wild video surveillance datasets where we outperform state-of-the-art appearance-based trackers. We also introduce a new challenging dataset with complex object appearance changes.Comment: Under review with the IEEE Transactions on Circuits and Systems for Video Technolog

Fundamental structures of dynamic social networks

Social systems are in a constant state of flux with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding spreading of influence or diseases, formation of friendships, and the productivity of teams. While there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the micro-dynamics of social networks. Here we explore the dynamic social network of a densely-connected population of approximately 1000 individuals and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geo-location, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection unnecessary. Starting from 5-minute time slices we uncover dynamic social structures expressed on multiple timescales. On the hourly timescale, we find that gatherings are fluid, with members coming and going, but organized via a stable core of individuals. Each core represents a social context. Cores exhibit a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores are preceded by coordination behavior in the communication networks, and demonstrating that social behavior can be predicted with high precision.Comment: Main Manuscript: 16 pages, 4 figures. Supplementary Information: 39 pages, 34 figure

Evaluating the Approach of Using NOx Control Performance Tracking for On-Board Diagnostics of Heavy-Duty Diesel Vehicles

egulatory agencies have taken several measures to ensure proper regulation of engine exhaust in response to a yearly rise in urban pollution levels. This is due in no small part to vehicular traffic and resulting air pollution from exhaust. This study evaluates the NOx Control Performance Tracking (NCPT) Onboard Diagnostic (OBD) parameter proposed by the California Air Resources Board (CARB) as a tool to assess in-use heavy-duty vehicle performance. It also assesses the various criteria prescribed in the NCPT approach for applicability to real-world vehicle data. In order to analyze the data, the study also investigated the effect of various filter constants values over the cumulative values binned into the various categories. The study also illustrates the differences in the bin statistics as a function of vehicle activity and it evaluates the applicability of the NCPT approach for evaluating Not-to-Exceed (NTE) operation. The collected data displayed abnormalities which could be attributed to sensor limitations. This project proposes two options to reduce the noise in the sensor’s data. In the first, it uses the NOx stable channel – if available – and the second is the exponentially weighted moving average (EWMA). Both reducing methods were then compared to the original raw dataset to ensure no over smoothing of the data occurred. Once these datasets were finalized, they went through the Moving-Average Window (MAW) method proposed by EURO VI regulations before they could be binned. The results indicate that despite applying different methods for NOx data reduction, the final binning product only displayed small change in value for certain bins while some remained intact. In addition, the vehicle displayed very few values inside the NTE zone, accounting at the most for 17% of the engine’s operation

Monte Carlo Simulations of Single-Molecule Fluorescence Detection Experiments

Several Monte Carlo simulations of single-molecule fluorescence systems are developed to help evaluate and improve ongoing experiments. In the first simulation, trapping of a single molecule in a nanochannel is studied. Molecules move along the nanochannel by diffusion and electrokinetic flow. Single-molecule fluorescence signals excited by two spatially offset laser beams are detected and the direction of the flow is adjusted to try to equalize the signals and center the molecule between the beams. An algorithm is evaluated for trapping individual molecules in succession by rapidly reloading the trap after a molecule photobleaches or escapes. This is shown to be effective for trapping fast-diffusing single-chromophore molecules in succession within a micron-sized confocal region while accommodating the limited electrokinetic speed and the finite latency of feedback imposed by experimental hardware. In the second simulation, trapping of a molecule in a two-dimensional fluidic device consisting of sub-micron-separated glass plates is studied. Two different illumination schemes for sensing the molecule\u27s position are compared: (i) a single continuous laser spot circularly scanned at 40 KHz or 240 KHz in the plane of the device; and (ii) four pulsed laser spots arranged in a square and temporally alternated at 304 MHz In either case, the times of detected photons are used by algorithms to control the electrokinetic flow in two dimensions to compensate diffusion and achieve single-molecule trapping. However each scheme is found to have limitations, as circular scanning produces a modulation in the fluorescence signal and in the autocorrelation function, whereas the four-pulse scheme becomes ineffective if the fluorescence lifetime of the molecule is greater than the time between laser pulses, The third simulation investigates appropriate conditions for detection of single molecules flowing through an array of fluidic channels for an application to high-throughput screening for pharmaceutical drug discovery. For parallelized single-molecule detection, illumination is provided by a continuous laser focused to a line intersecting all channels and fluorescence is imaged to a single row of pixels of an electron-multiplying CCD with sufficient gain for single-photon detection. The simulation separately models each channel to determine laser, flow, and camera operating conditions suitable for efficient detection