arXiv subjects

Bing Zhou

Publications and source records attributed to Bing Zhou.

At least 91 records · Page 5Linked to original sources

arXiv2019

Personality-Aware Probabilistic Map for Trajectory Prediction of Pedestrians

We present a novel trajectory prediction algorithm for pedestrians based on a personality-aware probabilistic feature map. This map is computed using a spatial query structure and each value represents the probability of the predicted pedestrian passing through various positions in the crowd space. We update this map dynamically based on the agents in the environment and prior trajectory of a pedestrian. Furthermore, we estimate the personality characteristics of each pedestrian and use them to improve the prediction by estimating the shortest path in this map. Our approach is general and works well on crowd videos with low and high pedestrian density. We evaluate our model on standard human-trajectory datasets. In practice, our prediction algorithm improves the accuracy by 5-9% over prior algorithms.

cs.GR↗

arXiv2019

Multi-scale discriminative Region Discovery for Weakly-Supervised Object Localization

Localizing objects with weak supervision in an image is a key problem of the research in computer vision community. Many existing Weakly-Supervised Object Localization (WSOL) approaches tackle this problem by estimating the most discriminative regions with feature maps (activation maps) obtained by Deep Convolutional Neural Network, that is, only the objects or parts of them with the most discriminative response will be located. However, the activation maps often display different local maximum responses or relatively weak response when one image contains multiple objects with the same type or small objects. In this paper, we propose a simple yet effective multi-scale discriminative region discovery method to localize not only more integral objects but also as many as possible with only image-level class labels. The gradient weights flowing into different convolutional layers of CNN are taken as the input of our method, which is different from previous methods only considering that of the final convolutional layer. To mine more discriminative regions for the task of object localization, the multiple local maximum from the gradient weight maps are leveraged to generate the localization map with a parallel sliding window. Furthermore, multi-scale localization maps from different convolutional layers are fused to produce the final result. We evaluate the proposed method with the foundation of VGGnet on the ILSVRC 2016, CUB-200-2011 and PASCAL VOC 2012 datasets. On ILSVRC 2016, the proposed method yields the Top-1 localization error of 48.65\%, which outperforms previous results by 2.75\%. On PASCAL VOC 2012, our approach achieve the highest localization accuracy of 0.43. Even for CUB-200-2011 dataset, our method still achieves competitive results.

cs.CV↗

arXiv2019

Design and performance of a TDC ASIC for the upgrade of the ATLAS Monitored Drift Tube detector

We present the prototype of a time-to-digital (TDC) ASIC for the upgrade of the ATLAS Monitored Drift Tube (MDT) detector for high-luminosity LHC operation. This ASIC is based on a previously submitted demonstrator ASIC designed for timing performance evaluation, and includes all features necessary for the various operation modes, as well as the migration to the TSMC 130 nm CMOS technology. We present the TDC design with the emphasis on added features and performance optimization. Tests of the timing performance demonstrate that this ASIC meets the design specifications. The TDC has a bin size of about 780 ps, and a timing bin variations within 40 ps for all 24 channels with leading and trailing edge digitization, while the power consumption has been limited to 250 mW, corresponding to a consumption of about 5.2 mW per edge measurement.

physics.ins-det↗

arXiv2019

Mass Production of a Trigger Data Serializer ASIC for the Upgrade of the Muon Spectrometer at the ATLAS Experiment

The Trigger Data Serializer (TDS) is a custom ASIC designed for the upgrade of the innermost station of the endcap ATLAS Muon Spectrometer. It is a mixed-signal chip with two working modes that can handle up to 128 detector channels. A total of 6,000 TDS ASICs have been produced for detector operation. This paper discusses a custom automatic test platform we developed to provide quality control of the TDS ASICs. We introduce the design, test procedures, and results obtained from this TDS testing platform.

physics.ins-det↗

arXiv2019

A Multi-Layer SEU Mitigation Strategy to Improve FPGA Design Robustness for the ATLAS Muon Spectrometer Upgrade

We present a multi-layer single-event upset mitigation strategy implemented in a low-cost Xilinx Artix-7 FPGA. The implementation is targeted for a trigger data router for the ATLAS muon spectrometer upgrade. The mitigation strategy employs three layers of protection to improve overall FPGA design robustness: use of triple-modular redundancy for FPGA fabric logic and embedded soft-error mitigation in the first layer; further enhancement with multi-boot FPGA reconfiguration across multiple copies of configuration memory in the second layer; and FPGA power cycling and configuration memory re-initialization in the third layer. The effectiveness of this scheme has been evaluated at two different neutron facilities, LANSCE and NCSR Demokritos, with 800 MeV and 25 MeV beam energies, respectively. Testing was performed with a similar configuration to that planned for final operation. We discuss the testing strategy and summarize the test results to estimate the expected data loss over 10 years of operation in the ATLAS experiment.

physics.ins-det↗

arXiv2019

Crowd Behavior Simulation with Emotional Contagion in Unexpected Multi-hazard Situations

In this paper we present a novel crowd simulation method by modeling the generation and contagion of panic emotion under multi-hazard circumstances. Specifically, we first classify hazards into different types (transient and persistent, concurrent and non-concurrent, static and dynamic ) based on their inherent characteristics. Then, we introduce the concept of perilous field for each hazard and further transform the critical level of the field to its invoked-panic emotion. After that, we propose an emotional contagion model to simulate the evolving process of panic emotion caused by multiple hazards in these situations. Finally, we introduce an Emotional Reciprocal Velocity Obstacles (ERVO) model to simulate the crowd behaviors by augmenting the traditional RVO model with emotional contagion, which combines the emotional impact and local avoidance together for the first time. Our experimental results show that this method can soundly generate realistic group behaviors as well as panic emotion dynamics in a crowd in multi-hazard environments.

cs.MA↗

arXiv2018

ALMA Observations of Ethyl Formate toward Orion KL

Orion KL is one of the prime templates of astrochemical and prebiotic chemical studies. We wish to explore more organic molecules with increasing complexity in this region. In particular, we have searched for one of the most complex organic molecules detected in space so far, ethyl formate (C$_{2}$H$_{5}$OCHO). This species is the next step in chemical complexity after the simplest member of esters (methyl formate, CH$_{3}$OCHO). The mechanisms leading to its formation are still poorly known. We have used high angular resolution ($\sim$ 1.$^{\prime\prime}$5) ALMA observations covering a large bandwidth from 214 to 247 GHz. We have detected 82 unblended lines of C$_{2}$H$_{5}$OCHO (49 and 33 of the trans and gauche conformers, respectively). The line images showed that C$_{2}$H$_{5}$OCHO arises mainly from the compact ridge and the hot core-southwest regions. The derived rotational temperatures and column densities are 122 $\pm$ 34 K, (0.9 $\pm$ 0.3) $\times$ 10$^{16}$ cm$^{-2}$ for the hot core-SW, and 103 $\pm$ 13 K, (0.6 $\pm$ 0.3) $\times$ 10$^{16}$ cm$^{-2}$ for the compact ridge. The comparison of spatial distribution and abundance ratios with chemically related molecules (methyl formate, ethanol and formic acid) indicates that C$_{2}$H$_{5}$OCHO is likely formed on the surface of dust grains by addition of CH$_{3}$ to functional-group radicals (CH$_{2}$OCHO) derived from methyl formate (CH$_{3}$OCHO).

astro-ph.SR↗

arXiv2018

Field-free Magnetization Switching by Utilizing the Spin Hall Effect and Interlayer Exchange Coupling of Iridium

Magnetization switching by spin-orbit torque (SOT) via spin Hall effect represents as a competitive alternative to that by spin-transfer torque (STT) used for magnetoresistive random access memory (MRAM), as it does not require high-density current to go through the tunnel junction. For perpendicular MRAM, however, SOT driven switching of the free layer requires an external in-plane field, which poses limitation for viability in practical applications. Here we demonstrate field-free magnetization switching of a perpendicular magnet by utilizing an Iridium (Ir) layer. The Ir layer not only provides SOTs via spin Hall effect, but also induce interlayer exchange coupling with an in-plane magnetic layer that eliminates the need for the external field. Such dual functions of the Ir layer allows future build-up of magnetoresistive stacks for memory and logic applications. Experimental observations show that the SOT driven field-free magnetization reversal is characterized as domain nucleation and expansion. Micromagnetic modeling is carried out to provide in-depth understanding of the perpendicular magnetization reversal process in the presence of an in-plane exchange coupling field.

cond-mat.mtrl-sci↗

arXiv2018

Abnormal Event Detection and Location for Dense Crowds using Repulsive Forces and Sparse Reconstruction

This paper proposes a method based on repulsive forces and sparse reconstruction for the detection and location of abnormal events in crowded scenes. In order to avoid the challenging problem of accurately tracking each specific individual in a dense or complex scene, we divide each frame of the surveillance video into a fixed number of grids and select a single representative point in each grid as the individual to track. The repulsive force model, which can accurately reflect interactive behaviors of crowds, is used to calculate the interactive forces between grid particles in crowded scenes and to construct a force flow matrix using these discrete forces from a fixed number of continuous frames. The force flow matrix, which contains spatial and temporal information, is adopted to train a group of visual dictionaries by sparse coding. To further improve the detection efficiency and avoid concept drift, we propose a fully unsupervised global and local dynamic updating algorithm, based on sparse reconstruction and a group of word pools. For anomaly location, since our method is based on a fixed grid, we can judge whether anomalies occur in a region intuitively according to the reconstruction error of the corresponding visual words. We experimentally verify the proposed method using the UMN dataset, the UCSD dataset and the Web dataset separately. The results indicate that our method can not only detect abnormal events accurately, but can also pinpoint the location of anomalies.

cs.CV↗

arXiv2018

Bi-directional Graph Structure Information Model for Multi-Person Pose Estimation

In this paper, we propose a novel multi-stage network architecture with two branches in each stage to estimate multi-person poses in images. The first branch predicts the confidence maps of joints and uses a geometrical transform kernel to propagate information between neighboring joints at the confidence level. The second branch proposes a bi-directional graph structure information model (BGSIM) to encode rich contextual information and to infer the occlusion relationship among different joints. We dynamically determine the joint point with highest response of the confidence maps as base point of passing message in BGSIM. Based on the proposed network structure, we achieve an average precision of 62.9 on the COCO Keypoint Challenge dataset and 77.6 on the MPII (multi-person) dataset. Compared with other state-of-art methods, our method can achieve highly promising results on our selected multi-person dataset without extra training.

cs.CV↗

arXiv2018

USAR: an Interactive User-specific Aesthetic Ranking Framework for Images

When assessing whether an image is of high or low quality, it is indispensable to take personal preference into account. Existing aesthetic models lay emphasis on hand-crafted features or deep features commonly shared by high quality images, but with limited or no consideration for personal preference and user interaction. To that end, we propose a novel and user-friendly aesthetic ranking framework via powerful deep neural network and a small amount of user interaction, which can automatically estimate and rank the aesthetic characteristics of images in accordance with users' preference. Our framework takes as input a series of photos that users prefer, and produces as output a reliable, user-specific aesthetic ranking model matching with users' preference. Considering the subjectivity of personal preference and the uncertainty of user's single selection, a unique and exclusive dataset will be constructed interactively to describe the preference of one individual by retrieving the most similar images with regard to those specified by users. Based on this unique user-specific dataset and sufficient well-designed aesthetic attributes, a customized aesthetic distribution model can be learned, which concatenates both personalized preference and aesthetic rules. We conduct extensive experiments and user studies on two large-scale public datasets, and demonstrate that our framework outperforms those work based on conventional aesthetic assessment or ranking model.

cs.CV↗

arXiv2018

Stylize Aesthetic QR Code

With the continued proliferation of smart mobile devices, Quick Response (QR) code has become one of the most-used types of two-dimensional code in the world. Aiming at beautifying the visual-unpleasant appearance of QR codes, existing works have developed a series of techniques. However, these works still leave much to be desired, such as personalization, artistry, and robustness. To address these issues, in this paper, we propose a novel type of aesthetic QR codes, SEE (Stylize aEsthEtic) QR code, and a three-stage approach to automatically produce such robust style-oriented codes. Specifically, in the first stage, we propose a method to generate an optimized baseline aesthetic QR code, which reduces the visual contrast between the noise-like black/white modules and the blended image. In the second stage, to obtain art style QR code, we tailor an appropriate neural style transformation network to endow the baseline aesthetic QR code with artistic elements. In the third stage, we design an error-correction mechanism by balancing two competing terms, visual quality and readability, to ensure the performance robust. Extensive experiments demonstrate that SEE QR code has high quality in terms of both visual appearance and robustness, and also offers a greater variety of personalized choices to users.

cs.MM↗

arXiv2018

Depth Information Guided Crowd Counting for Complex Crowd Scenes

It is important to monitor and analyze crowd events for the sake of city safety. In an EDOF (extended depth of field) image with a crowded scene, the distribution of people is highly imbalanced. People far away from the camera look much smaller and often occlude each other heavily, while people close to the camera look larger. In such a case, it is difficult to accurately estimate the number of people by using one technique. In this paper, we propose a Depth Information Guided Crowd Counting (DigCrowd) method to deal with crowded EDOF scenes. DigCrowd first uses the depth information of an image to segment the scene into a far-view region and a near-view region. Then Digcrowd maps the far-view region to its crowd density map and uses a detection method to count the people in the near-view region. In addition, we introduce a new crowd dataset that contains 1000 images. Experimental results demonstrate the effectiveness of our DigCrowd method

cs.CV↗

arXiv2018

The effect of adding magnetic oxide as grain boundary for HAMR

Grain-to-grain Curie temperature (Tc) variation in the media reduces signal-to-noise ratio due to its contribution in transition jitter noise, especially when average grain size is pushing down to increase the area storage capacity. A thermally insulating magnetic grain boundary may suppress such grain-to-grain Tc variation, especially at small grain size. Here we present an experimental study on the effect of adding thermally-insulating magnetic oxide, in particular BaFexOy, as part of the grain boundary materials in granular FePt-C HAMR media. It is found that the BaFexOy is chemically inert to FePt and the chemical ordering of FePt-BaFexOy-C media are similar to that of FePt-C meida. By tuning the volume fraction of BaFexOy and C, well-separated FePt grains (average grain size = 6.8 nm) surrounded by BaFexOy shell with perpendicular Hc above 35 kOe can be obtained. Transmission electron microscopy study with chemical analysis shows that the magnetic oxide appears to be crystalline and surround the FePt grains with immediate full enclosure. Magnetic measurements indicate an effective increase of magnetic grain size at temperatures below FePt Curie temperature. Pulsed laser pump-probe measurement indicates a measurable reduction of Curie temperature variation for the FePt-BaFexOy-C media with carefully comparison with the reference FePt-C media.

cond-mat.mtrl-sci↗

arXiv2018

ART-UP: A Novel Method for Generating Scanning-robust Aesthetic QR codes

QR codes are usually scanned in different environments, so they must be robust to variations in illumination, scale, coverage, and camera angles. Aesthetic QR codes improve the visual quality, but subtle changes in their appearance may cause scanning failure. In this paper, a new method to generate scanning-robust aesthetic QR codes is proposed, which is based on a module-based scanning probability estimation model that can effectively balance the tradeoff between visual quality and scanning robustness. Our method locally adjusts the luminance of each module by estimating the probability of successful sampling. The approach adopts the hierarchical, coarse-to-fine strategy to enhance the visual quality of aesthetic QR codes, which sequentially generate the following three codes: a binary aesthetic QR code, a grayscale aesthetic QR code, and the final color aesthetic QR code. Our approach also can be used to create QR codes with different visual styles by adjusting some initialization parameters. User surveys and decoding experiments were adopted for evaluating our method compared with state-of-the-art algorithms, which indicates that the proposed approach has excellent performance in terms of both visual quality and scanning robustness.

cs.MM↗

arXiv2018

Efficiently Disassemble-and-Pack for Mechanism

In this paper, we present a disassemble-and-pack approach for a mechanism to seek a box which contains total mechanical parts with high space utilization. Its key feature is that mechanism contains not only geometric shapes but also internal motion structures which can be calculated to adjust geometric shapes of the mechanical parts. Our system consists of two steps: disassemble mechanical object into a group set and pack them within a box efficiently. The first step is to create a hierarchy of possible group set of parts which is generated by disconnecting the selected joints and adjust motion structures of parts in groups. The aim of this step is seeking total minimum volume of each group. The second step is to exploit the hierarchy based on breadth-first-search to obtain a group set. Every group in the set is inserted into specified box from maximum volume to minimum based on our packing strategy. Until an approximated result with satisfied efficiency is accepted, our approach finish exploiting the hierarchy.

cs.CG↗

arXiv2017

Development of a time-to-digital converter ASIC for the upgrade of the ATLAS Monitored Drift Tube detector

The upgrade of the ATLAS muon spectrometer for high-luminosity LHC requires new trigger and readout electronics for the various elements of the detector. We present the design of a time-to-digital converter (TDC) ASIC prototype for the ATLAS Monitored Drift Tube (MDT) detector. The chip was fabricated in a GlobalFoundries 130 nm CMOS technology. Studies indicate that its timing and power consumption characteristics meet the design specifications, with a timing bin variation of 40 ps for all 48 channels with a power consumption of about 6.5 mW per channel.

physics.ins-det↗

arXiv2017

A Programmable Time Alignment Scheme for Detector Signals from the Upgraded muon Spectrometer at the ATLAS Experiment

We present a programmable time alignment scheme used in an ASIC for the ATLAS forward muon trigger development. The scheme utilizes regenerated clocks with programmable phases to compensate for the timing offsets introduced by different detector trace lengths. Each ASIC used in the design has 104 input channels with delay compensation circuitry providing steps of ~ 3 ns and a full range of 25 ns for each channel. Detailed implementation of the scheme including majority logic to suppress single-event effects is presented. The scheme is flexible and fully synthesizable. The approach is adaptable to other applications with similar phase shifting requirements. In addition, the design is resource efficient and is suitable for cost-effective digital implementation with a large number of channels.

physics.ins-det↗