Jun Luo

Jun Luo
Nanyang Technological University | ntu · School of Computer Science and Engineering

PhD (EPFL)

About

166
Publications
55,697
Reads
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6,886
Citations
Introduction
Dr. Jun Luo currently works at the School of Computer Engineering, Nanyang Technological University. Jun does research in Mobile and Distributed Computing, Deep Learning and Computer Vision, as well as Applied Operations Research. His current focuses lie on 1) Contact-free Sensing Driven by Deep Learning, 2) Visible Light Communication and Sensing, 3) Indoor and Outdoor Localization and Tracking, and 4) Application of Machine Learning to Mobile Computing and Networking.
Additional affiliations
August 2014 - present
Nanyang Technological University
Position
  • Professor (Associate)
December 2008 - August 2014
Nanyang Technological University
Position
  • Professor (Assistant)
October 2006 - November 2008
University of Waterloo
Position
  • Research Associate
Education
October 2000 - April 2006
École Polytechnique Fédérale de Lausanne
Field of study
  • Computer Science

Publications

Publications (166)
Conference Paper
Full-text available
Whereas a few physical layer techniques have been proposed to locate a signal source indoors, they all deem multipath a "curse" and hence take great efforts to cope with it. Consequently, each sensor only obtains the information about the direct path; this necessitates a networked sensing system (hence higher system complexity and deployment cost)...
Conference Paper
Full-text available
Given the ever-expanding scale of WiFi deployments in metropolitan areas, we have reached the point where accurate GPS-free outdoor localization becomes possible by relying solely on the WiFi infrastructure. Nevertheless, the existing industrial practices do not seem to have the right implementation to achieve an adequate accuracy, while the academ...
Article
Full-text available
Big data processing has emerged as an important analytical tool for governments and multinational corporations. The traditional wisdom calls for the collection of all the data across the world to a central data center location, to be processed using data-parallel applications. This is neither efficient nor practical as the volume of data grows expo...
Article
Full-text available
Mobile crowdsensing has been considered as a promising approach for large scale urban data collection, but has also posed new challenging problems, such as incentivization and quality control. Among the other incentivization approaches, posted pricing has been widely adopted by commercial systems due to the reason that it naturally achieves truthfu...
Article
Full-text available
Recent large-scale deployments of wireless sensor networks have posed a high demand on network throughput, forcing all (discrete) orthogonal ZigBee channels to be exploited to enhance transmission parallelism. However, the interference from widely deployed WiFi networks has severely jeopardized the usability of these discrete ZigBee channels, while...
Conference Paper
Full-text available
Optical camera communication (OCC) enabled by LED and embedded cameras has attracted extensive attention, thanks to its rich spectrum availability and ready deployability. However, the close interactions between OCC and the indoor spaces have created two major challenges. On one hand, the stripe pattern incurred by OCC may greatly damage the accura...
Article
Full-text available
Aerial acoustic communication attracts substantial attention for its simplicity, cost-effectiveness, and power-efficiency. Unfortunately, the preferred inaudible transmission has to strike a balance between the transmission rate and communication range, when the Bit-Error-Rate (BER) is under a certain threshold. Additionally, the performance of pre...
Article
Full-text available
Continuous respiration monitoring is significant for real-life healthcare applications, but realizing it is extremely hard as wearable sensors are cumbersome and contact-free sensors largely fail to tolerate user movements. Meanwhile, tracking users indoors mostly demands user-held devices, while device-free localization can barely tell what and wh...
Article
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In this paper we study the problem of passive human localization using an infrared (IR) thermal imaging camera which detects IR radiation emitted by human without carry-on devices and thereby generates a heat map of human body. Rather than directly using the heat map, we propose to exploit temperature of human body and design a lightweight approach...
Article
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As mobile shopping has gradually become the mainstream shopping mode, recommendation systems are gaining an increasingly wide adoption. Existing recommendation systems are mainly based on explicit and implicit user behaviors. However, these user behaviors may not directly indicate users' inner feelings, causing erroneous user preference estimation...
Conference Paper
Full-text available
Contact-free vital-signs monitoring enabled by radio frequency (RF) sensing is gaining increasing attention, thanks to its non-intrusiveness, noise-resistance, and low cost. Whereas most of these systems only perform respiration monitoring or retrieve heart rate, few can recover fine-grained heartbeat waveform. The major reason is that, though both...
Conference Paper
Full-text available
Proliferation of smart environments entails the need for real-time and ubiquitous human-machine interactions through, mostly likely, hand/arm motions. Though a few recent efforts attempt to track hand/arm motions in real-time with COTS devices, they either obtain a rather low accuracy or have to rely on a carefully designed infrastructure and some...
Article
Full-text available
We propose a robust, anisotropic normal estimation method for both point clouds and meshes using a low rank matrix approximation algorithm. First, we compute a local feature descriptor for each point and find similar, non-local neighbors that we organize into a matrix. We then show that a low rank matrix approximation algorithm can robustly estimat...
Article
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Both voice communication and automatic speech verification (ASV) over smart devices are vulnerable to voice impersonation (VI) attack, which is often launched via imitating a target's voice characteristics to deceive human auditory sense or fool the ASV system. Researchers have designed a number of defense schemes yet without consideration of unive...
Article
Full-text available
With the proliferation of Internet-of-Things (IoT) devices, acoustic sensing attracts significant attention in recent years. It exploits acoustic transceivers such as microphones and speakers beyond their primary functions, namely recording and playing, to enable novel applications and new user experiences. In this paper, we present the first syste...
Conference Paper
Full-text available
Being able to see into walls is crucial for diagnostics of building health; it enables inspections of wall structure without undermining the structural integrity. However, existing sensing devices do not seem to offer a full capability in mapping the in-wall structure while identifying their status (e.g., seepage and corrosion). In this paper, we d...
Conference Paper
Full-text available
Vital signs are crucial indicators for human health, and researchers are studying contact-free alternatives to existing wearable vital signs sensors. Unfortunately, most of these designs demand a subject human body to be relatively static, rendering them very inconvenient to adopt in practice where body movements occur frequently. In particular, ra...
Conference Paper
Full-text available
Radio frequency (RF) technologies have achieved a great success in data communication. In recent years, pervasive RF signals are further exploited for sensing; RF sensing has since attracted attentions from both academia and industry. Existing developments mainly employ commodity Wi-Fi hardware or rely on sophisticated SDR platforms. While promisin...
Preprint
Full-text available
Whereas adversarial training can be useful against specific adversarial perturbations, they have also proven ineffective in generalizing towards attacks deviating from those used for training. However, we observe that this ineffectiveness is intrinsically connected to domain adaptability, another crucial issue in deep learning for which adversarial...
Conference Paper
Full-text available
Crucial for healthcare and biomedical applications, respiration monitoring often employs wearable sensors in practice, causing inconvenience due to their direct contact with human bodies. Therefore, researchers have been constantly searching for contact-free alternatives. Nonetheless, existing contact-free designs mostly require human subjects to r...
Article
Full-text available
Though measuring ambient temperature is often deemed as an easy job, collecting large-scale temperature readings in real-time is still a formidable task. The recent boom of network-ready (mobile) devices and the subsequent mobile crowdsourcing applications do offer an opportunity to accomplish this task, yet equipping commodity devices with ambient...
Article
Full-text available
Acoustic sensing has attracted significant attention recently, thanks to the pervasive availability of device support. However, adopting consumer-grade devices (e.g., smartphones) to deploy acoustic sensing applications faces the challenge of device/OS heterogeneity. Researchers have to pay tremendous efforts in tackling platform-dependent details...
Article
Full-text available
Indoor localization is crucial to enable context-aware applications, but existing solutions mostly require a user to carry a device, so as to actively sense location-discriminating signals. However, many applications do not prefer user involvement due to, e.g., the cumbersome of carrying a device. Therefore, solutions that track user locations pass...
Article
Full-text available
Deemed as a practical approach to realize Visible Light Communication on commercial-off-the-shelf devices, the Optical Camera Communication (OCC) is attracting increasing attention, thanks to its readiness to be built purely upon ubiquitous LED illuminating infrastructure and handy smartphones. However, limited by the low sampling ability of the bu...
Preprint
Full-text available
Recently, \textit{passive behavioral biometrics} (e.g., gesture or footstep) have become promising complements to conventional user identification methods (e.g., face or fingerprint) under special situations, yet existing sensing technologies require lengthy measurement traces and cannot identify multiple users at the same time. To this end, we pro...
Article
Full-text available
Human Activity Recognition (HAR) plays a critical role in a wide range of real-world applications, and it is traditionally achieved via wearable sensing. Recently, to avoid the burden and discomfort caused by wearable devices, device-free approaches exploiting Radio-Frequency (RF) signals arise as a promising alternative for HAR. Most of the latest...
Article
Full-text available
Temperature is an important data source for weather forecasting, agriculture irrigation, anomaly detection, etc. Whereas temperature measurement can be achieved via low-cost yet standalone hardware with reasonable accuracy, integrating thermal sensing into ubiquitous computing devices is highly non-trivial due to the design requirement for specific...
Article
Full-text available
Visible Light Communication (VLC) systems relying on commercial-off-the-shelf (COTS) devices have gathered momentum recently, due to the pervasive adoption of LED lighting and mobile devices. However, the achievable throughput by such practical systems is still several orders below those claimed by controlled experiments with specialized devices. I...
Article
Full-text available
The mobile crowdsensing paradigm facilitates a broad range of emerging sensing applications by leveraging ubiquitous mobile users to cooperatively perform certain sensing tasks with their smart devices. As this paradigm involves data collection from users, the issue of designing rewards to incentivize users is fundamentally important to ensure part...
Article
Full-text available
Given an undirected graph and a number of vertex groups, the group Steiner tree problem is to find a tree such that (i) this tree contains at least one vertex in each vertex group; and (ii) the sum of vertex and edge weights in this tree is minimized. Solving this problem is useful in various scenarios, ranging from social networks to knowledge gra...
Article
Full-text available
In recent years, (Radio Frequency) RF sensing has gained increasing popularity due to its pervasiveness, low-cost, non-intrusiveness, and privacy preservation. However, realizing the promises of RF sensing is highly non-trivial, given typical challenges such as multipath and interference. One potential solution leverages deep learning to build dire...
Article
Full-text available
Owing to the ubiquitous penetration of Wi-Fi in our daily lives, Wi-Fi indoor localization has attracted intensive attentions in the last decade or so. Despite some significant progresses, the high accuracy of existing systems is still achieved at the cost of dense access point (AP) deployment. The more practical single AP localization is largely l...
Article
Full-text available
Multiple blind sound source localization is the key technology for a myriad of applications such as robotic navigation and indoor localization. However, existing solutions can only locate a few sound sources simultaneously due to the limitation imposed by the number of microphones in an array. To this end, this paper proposes a novel multiple blind...
Conference Paper
Full-text available
Though measuring ambient temperature is often deemed as an easy job, collecting large-scale temperature readings in real-time is still a formidable task. The recent boom of network-ready (mobile) devices and the subsequent mobile crowdsourcing applications do offer an opportunity to accomplish this task, yet equipping commodity devices with ambient...
Conference Paper
Full-text available
An ability to detect, classify, and locate complex acoustic events can be a powerful tool to help smart systems build context-awareness, e.g., to make rich inferences about human behaviors in physical spaces. Conventional methods to measure acoustic signals employ microphones as sensors. As signals from multiple acoustic sources are blended during...
Conference Paper
Full-text available
Radio-Frequency (RF) based device-free Human Activity Recognition (HAR) rises as a promising solution for many applications. However, device-free (or contactless) sensing is often more sensitive to environment changes than device-based (or wearable) sensing. Also, RF datasets strictly require on-line labeling during collection, starkly different fr...
Article
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The extremely high frequency of Millimeter-Wave technology warrants Gbps throughput for the next-generation wireless communication systems, but mmWave signals also suffer from severe path loss due to high attenuation. To compensate for this loss, mmWave radios establish communication links via directional beams so as to increase channel gains and c...
Chapter
Incentive mechanisms are pivotal in encouraging mobile users to participate to contribute their sensing information. However, most studies on incentive mechanisms merely considered individual behaviors of the users rather than their interdependency. The interdependent behaviors of the users are common as they originate from the social network effec...
Article
Full-text available
In this Letter, we propose and demonstrate a practical optical-spatial-summing-based non-orthogonal multiple access (OSS-NOMA) technique for visible light communication (VLC) systems. This technique is innovative in adopting OSS in that the transmitter of OSS-NOMA VLC can be built upon commercial illuminating light emitting diodes (LEDs), free of L...
Article
Full-text available
Given the significant amount of time people spend in vehicles, health issues under driving condition have become a major concern. Such issues may vary from fatigue, asthma, stroke, to even heart attack, yet they can be adequately indicated by vital signs and abnormal activities. Therefore, in-vehicle vital sign monitoring can help us predict and he...
Conference Paper
Full-text available
Whereas adversarial training is employed as the main defence strategy against specific adversarial samples, it has limited generalization capability and incurs excessive time complexity. In this paper, we propose an attack-agnostic defence framework to enhance the intrinsic robustness of neural networks, without jeopardizing the ability of generali...
Preprint
Full-text available
Whereas adversarial training is employed as the main defence strategy against specific adversarial samples, it has limited generalization capability and incurs excessive time complexity. In this paper, we propose an attack-agnostic defence framework to enhance the intrinsic robustness of neural networks, without jeopardizing the ability of generali...
Article
Full-text available
Bump hunting is an important approach to the extraction of insights from Euclidean datasets. Recently, it has been explored for graph datasets for the first time, and a single bump is hunted in an unweighted graph in this exploration. Here, we extend this exploration by hunting multiple bumps in a weighted graph. Given a weighted graph and a set of...
Article
Full-text available
Whereas the increasing popularity of both commercial light-emitting diode (LED) lighting and mobile devices certainly creates opportunity for real-life deployment of visible light communication (VLC) systems, reaching the high throughput promised by lab experiments still faces major obstacles. In particular, lacking the sophisticated hardware and s...
Article
Full-text available
Most existing proposals for indoor localization are “unnatural”, as they rely on sensing abilities not available to human beings. While such a mismatch causes complications in human-computer interactions and thus potentially reduces the usability and friendliness of a localization service, it is partially entailed by the need for low-cost/effort se...
Article
Full-text available
Commercial-off-the-shelf (COTS) devices enabled visible light communication (VLC) for Internet of things (IoT) applications has attracted extensive attentions from both academic and industrial communities, thanks to the pervasive deployments of light emitting diode (LED) lighting infrastructure. However, due to the limitation of frequency response...
Article
Full-text available
Articulated skeleton extraction or learning has been extensively studied for 2D (e.g., images and video) and 3D (e.g., volume sequences, motion capture, and mesh sequences) data. Nevertheless, robustly and accurately learning 3D articulated skeletons from point set sequences captured by a single consumer-grade depth camera still remains challenging...
Article
Full-text available
Traditional crowdsensing platforms rely on sensory information collected from a group of independent users or sensors. Recently, socially aware crowdsensing services have been introduced as the integration of social networks and crowdsensing platforms. For example, in health-related crowdsensing applications, a user benefits from information regard...
Conference Paper
Full-text available
Visible Light Communication (VLC) systems relying on commercial-off-the-shelf (COTS) devices have gathered momentum recently, due to the pervasive adoption of LED lighting and mobile devices. However, the achievable throughput by such practical systems is still several orders below those claimed by controlled experiments with specialized devices. I...
Article
Recently, Mobile Crowdsourcing (MC) has aroused great interest on the part of both academic and industrial circles. One of the key problems in MC is designing the proper mechanisms to incentivize user participation, as users are typically self-interested and must consume a substantial amount of MC resources/costs. Although considerable research has...
Article
The ever-expanding scale of WiFi deployments in metropolitan areas has made accurate GPS-free outdoor localization become possible by relying solely on the WiFi infrastructure. Nevertheless, neither academic researches nor existing industrial practices seem to provide a satisfactory solution or implementation. In this paper, we propose WOLoc (WiFi-...
Article
Full-text available
LED-Camera Visible Light Communication (VLC) is gaining increasing attention, thanks to its readiness to be implemented with Commercial Off-The-Shelf devices and its potential to deliver pervasive data services indoors. Nevertheless, existing LED-Camera VLC systems employ mainly low-order modulations such as On-Off Keying (OOK) given the simplicity...
Article
Full-text available
Mobile crowdsensing has shown a great potential to address large-scale data sensing problems by allocating sensing tasks to pervasive mobile users. The mobile users will participate in a crowdsensing platform if they can receive a satisfactory reward. In this paper, to recruit effectively and efficiently sufficient number of mobile users, i.e., par...