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Articles 5251 - 5280 of 8762
Full-Text Articles in Entire DC Network
Deduplication On Encrypted Big Data In Cloud, Zheng Yan, Wenxiu Ding, Xixun Yu, Haiqi Zhu, Deng, Robert H.
Deduplication On Encrypted Big Data In Cloud, Zheng Yan, Wenxiu Ding, Xixun Yu, Haiqi Zhu, Deng, Robert H.
Research Collection School Of Computing and Information Systems
Cloud computing offers a new way of service provision by re-arranging various resources over the Internet. The most important and popular cloud service is data storage. In order to preserve the privacy of data holders, data are often stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for big data storage and processing in cloud. Traditional deduplication schemes cannot work on encrypted data. Existing solutions of encrypted data deduplication suffer from security weakness. They cannot flexibly support data access control and revocation. Therefore, few of them can be readily …
Poster: A Device-Free Evaluation System For Gymnastics Using Passive Rfid Tags, Binbin Xie, Jie Xiong, Dingyi Fang, Xiaojiang Chen, Anwen Wang, Zhanyong Tang
Poster: A Device-Free Evaluation System For Gymnastics Using Passive Rfid Tags, Binbin Xie, Jie Xiong, Dingyi Fang, Xiaojiang Chen, Anwen Wang, Zhanyong Tang
Research Collection School Of Computing and Information Systems
No abstract provided.
Poster: Sonicnect: Accurate Hands-Free Gesture Input System With Smart Acoustic Sensing, Maotian Chang, Ping Li, Panlong Yang, Jie Xiong, Chang Tian
Poster: Sonicnect: Accurate Hands-Free Gesture Input System With Smart Acoustic Sensing, Maotian Chang, Ping Li, Panlong Yang, Jie Xiong, Chang Tian
Research Collection School Of Computing and Information Systems
This work presents Sonicnect, an acoustic sensing system with smartphone that enables accurate hands-free gesture input. Sonicnect leverages the embedded microphone in the smartphone to capture the subtle audio signals generated with fingers touching on the table. It supports 9 commonly used gestures (click, flip, scroll and zoom, etc) with above 92% recognition accuracy, and the minimum gesture movement could be 2cm. Distinguishable features are then extracted by exploiting spatio-temporal and frequency properties of the subtle audio signals. We conduct extensive real environment experiments to evaluate its performance. The results validate the effectiveness and robustness of Sonicnect.
Dual Formulations For Optimizing Dec-Pomdp Controllers, Akshat Kumar, Hala Mostafa, Shlomo Zilberstein
Dual Formulations For Optimizing Dec-Pomdp Controllers, Akshat Kumar, Hala Mostafa, Shlomo Zilberstein
Research Collection School Of Computing and Information Systems
Decentralized POMDP is an expressive model for multi-agent planning. Finite-state controllers (FSCs)---often used to represent policies for infinite-horizon problems---offer a compact, simple-to-execute policy representation. We exploit novel connections between optimizing decentralized FSCs and the dual linear program for MDPs. Consequently, we describe a dual mixed integer linear program (MIP) for optimizing deterministic FSCs. We exploit the Dec-POMDP structure to devise a compact MIP and formulate constraints that result in policies executable in partially-observable decentralized settings. We show analytically that the dual formulation can also be exploited within the expectation maximization (EM) framework to optimize stochastic FSCs. The resulting EM algorithm …
Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau
Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Evolutionary Algorithm is a well-known meta-heuristics paradigm capable of providing high-quality solutions to computationally hard problems. As with the other meta-heuristics, its performance is often attributed to appropriate design choices such as the choice of crossover operators and some other parameters. In this chapter, we propose a continuous state Markov Decision Process model to select crossover operators based on the states during evolutionary search. We propose to find the operator selection policy efficiently using a self-organizing neural network, which is trained offline using randomly selected training samples. The trained neural network is then verified on test instances not used for …
Geometric Aspects And Auxiliary Features To Top-K Processing [Advanced Seminar], Kyriakos Mouratidis
Geometric Aspects And Auxiliary Features To Top-K Processing [Advanced Seminar], Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Top-k processing is a well-studied problem with numerous applications that is becoming increasingly relevant with the growing availability of recommendation systems and decision making software on PCs, PDAs and smart-phones. The objective of this seminar is twofold. First, we will delve into the geometric aspects of top-k processing. Second, we will cover complementary features to top-k queries that have a strong geometric nature. The seminar will close with insights in the effect of dimensionality on the meaningfulness of top-k queries, and interesting similarities to nearest neighbor search.
An Experimental Investigation Of Product Competition And Marketing In Social Networks, Cen Chen, Zhiling Guo, Shih-Fen Cheng, Hoong Chuin Lau
An Experimental Investigation Of Product Competition And Marketing In Social Networks, Cen Chen, Zhiling Guo, Shih-Fen Cheng, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We conduct computational experiment using Facebook data to evaluate competing firms’ initial market seeding and subsequent targeted marketing strategies that influence consumers’ new product adoption decisions. We find that firms generally overspend their advertising budget in the market seeding phase. In the subsequent market advertising phase, a coupon strategy (equivalent to price discount) generally yields higher market share than the strategy of distributing free product samples. The effect is more significant when both price and product quality are low. We offer managerial insights into firms’ effective competition strategies for new product introduction in the presence of consumers’ word of mouth …
An Economic Analysis Of Consumer Learning For Online Entertainment Shopping, Jin Li, Zhiling Guo, Geoffrey K.F. Tso
An Economic Analysis Of Consumer Learning For Online Entertainment Shopping, Jin Li, Zhiling Guo, Geoffrey K.F. Tso
Research Collection School Of Computing and Information Systems
Entertainment shopping supported by pay-to-bid auction is an emerging online business model in recent years. Consumers expect both entertainment value and monetary return from their participation in entertainment shopping. We propose a dynamic structural model to study consumers’ online shopping behavior. We analyze the learning process of consumers from two perspectives based on the Bayesian updating framework: (1) consumers update their beliefs about the entertainment value through their repeated personal participation experiences, and (2) consumers infer the expected monetary payoffs on the website by observing the publically available auction ending price information. We estimate the model using a large dataset …
Learning Natural Language Inference With Lstm, Shuohang Wang, Jing Jiang
Learning Natural Language Inference With Lstm, Shuohang Wang, Jing Jiang
Research Collection School Of Computing and Information Systems
Natural language inference (NLI) is a fundamentally important task in natural language processing that has many applications. The recently released Stanford Natural Language Inference (SNLI) corpus has made it possible to develop and evaluate learning-centered methods such as deep neural networks for natural language inference (NLI). In this paper, we propose a special long short-term memory (LSTM) architecture for NLI. Our model builds on top of a recently proposed neural attention model for NLI but is based on a significantly different idea. Instead of deriving sentence embeddings for the premise and the hypothesis to be used for classification, our solution …
Efficient Multi-Class Selective Sampling On Graphs, Peng Yang, Peilin Zhao, Zhen Hai, Wei Liu, Hoi, Steven C. H., Xiao-Li Li
Efficient Multi-Class Selective Sampling On Graphs, Peng Yang, Peilin Zhao, Zhen Hai, Wei Liu, Hoi, Steven C. H., Xiao-Li Li
Research Collection School Of Computing and Information Systems
A graph-based multi-class classification problem is typically converted into a collection of binary classification tasks via the one-vs.-all strategy, and then tackled by applying proper binary classification algorithms. Unlike the one-vs.-all strategy, we suggest a unified framework which operates directly on the multi-class problem without reducing it to a collection of binary tasks. Moreover, this framework makes active learning practically feasible for multi-class problems, while the one-vs.-all strategy cannot. Specifically, we employ a novel randomized query technique to prioritize the informative instances. This query technique based on the hybrid criterion of "margin" and "uncertainty" can achieve a comparable mistake bound …
Demo: Wearable Application To Manage Problem Behavior In Children With Neurodevelopmental Disorders, Camellia Zakaria, Richard C. Davis
Demo: Wearable Application To Manage Problem Behavior In Children With Neurodevelopmental Disorders, Camellia Zakaria, Richard C. Davis
Research Collection School Of Computing and Information Systems
Managing problem behaviors in children with neurodevelopmental disorders can be challenging. Such behaviors may discourage social participation and learning. Many of these behaviors warrant intervention, however, are challenging for caregivers to constantly supervise. Previous work focused on developing recognition systems for stereotypical and aggressive behaviors. Researchers also developed visualization interface for caregivers to better understand their child’s needs. Our goal however, is to design an independent behavior management application to help children manage problem behaviors with minimal supervision.We conducted a field study at a school for children with special needs in Singapore, and interviewed ten teachers. This study helped us …
Demo: Ta$Ker: Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Thivya Kandappu, Randy Tandriansyah, Archan Misra
Demo: Ta$Ker: Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Thivya Kandappu, Randy Tandriansyah, Archan Misra
Research Collection School Of Computing and Information Systems
We design and develop TA$Ker, a real-world mobile crowd- sourcing platform to empirically study the worker responses to various task recommendation and selection strategies.
Automated Identification Of High Impact Bug Reports Leveraging Imbalanced Learning Strategies, Xinli Yang, David Lo, Qiao Huang, Xin Xia, Jianling Sun
Automated Identification Of High Impact Bug Reports Leveraging Imbalanced Learning Strategies, Xinli Yang, David Lo, Qiao Huang, Xin Xia, Jianling Sun
Research Collection School Of Computing and Information Systems
In practice, some bugs have more impact than others and thus deserve more immediate attention. Due to tight schedule and limited human resource, developers may not have enough time to inspect all bugs. Thus, they often concentrate on bugs that are highly impactful. In the literature, high impact bugs are used to refer to the bugs which appear in unexpected time or locations and bring more unexpected effects, or break pre-existing functionalities and destroy the user experience. Unfortunately, identifying high impact bugs from the thousands of bug reports in a bug tracking system is not an easy feat. Thus, an …
Mobipot: Understanding Mobile Telephony Threats With Honeycards, Marco Balduzzi, Payas Gupta, Lion Gu, Debin Gao, Mustaque Ahamad
Mobipot: Understanding Mobile Telephony Threats With Honeycards, Marco Balduzzi, Payas Gupta, Lion Gu, Debin Gao, Mustaque Ahamad
Research Collection School Of Computing and Information Systems
Over the past decade, the number of mobile phones has increased dramatically, overtaking the world population in October 2014. In developing countries like India and China, mobile subscribers outnumber traditional landline users and account for over 90% of the active population. At the same time, convergence of telephony with the Internet with technologies like VoIP makes it possible to reach a large number of telephone users at a low or no cost via voice calls or SMS (short message service) messages. As a consequence, cybercriminals are abusing the telephony channel to launch attacks, e.g., scams that offer fraudulent services and …
Cace: Exploiting Behavioral Interactions For Improved Activity Recognition In Multi-Inhabitant Smart Homes, Mohammad Arif Ul Alam, Nirmalya Roy, Archan Misra, Joseph Taylor
Cace: Exploiting Behavioral Interactions For Improved Activity Recognition In Multi-Inhabitant Smart Homes, Mohammad Arif Ul Alam, Nirmalya Roy, Archan Misra, Joseph Taylor
Research Collection School Of Computing and Information Systems
We propose CACE (Constraints And Correlations mining Engine) which investigates the challenges of improving the recognition of complex daily activities in multi-inhabitant smart homes, by better exploiting the spatiotemporal relationships across the activities of different individuals. We first propose and develop a loosely-coupled Hierarchical Dynamic Bayesian Network (HDBN), which both (a) captures the hierarchical inference of complex (macro-activity) contexts from lower-layer microactivity context (postural and improved oral gestural context), and (b) embeds the various types of behavioral correlations and constraints (at both micro-and macro-activity contexts) across the individuals. While this model is rich in terms of accuracy, it is computationally …
Poster: Improving Communication And Communicability With Smarter Use Of Text-Based Messages On Mobile And Wearable Devices, Kenny T. W. Choo
Poster: Improving Communication And Communicability With Smarter Use Of Text-Based Messages On Mobile And Wearable Devices, Kenny T. W. Choo
Research Collection School Of Computing and Information Systems
While smartphones have undoubtedly afforded many modern conveniences such as emails, instant messaging or web search, the notifications from smartphones conversely impact our lives through a deluge of information, or stress arising from expectations that we should turn our immediate attention to them (e.g., work emails). In my latest research, we find that the glanceability of smartwatches may provide an opportunity to reduce the perceived disruption from mobile notifications. Text is a common medium for communication in smart devices, the application of natural language processing on text, together with the physical affordances of smartwatches, present exciting opportunities for research to …
Poster: Air Quality Friendly Route Recommendation System, Savina Singla, Divya Bansal, Archan Misra
Poster: Air Quality Friendly Route Recommendation System, Savina Singla, Divya Bansal, Archan Misra
Research Collection School Of Computing and Information Systems
To model the overall personal inhalation of hazardous gases through the air (both indoor and outdoor) by an individual, provide air quality friendly route recommendations, thus raising the overall quality of urban movement and living healthy life.
Demo: Smartwatch Based Shopping Gesture Recognition, Meeralakshmi Radhakrishnan, Sharanya Eswaran, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan
Demo: Smartwatch Based Shopping Gesture Recognition, Meeralakshmi Radhakrishnan, Sharanya Eswaran, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
In the current retail segment, the retail store owners are keen to understand the browsing behavior and purchase pattern of the shoppers inside the physical stores. Profiling the behavior of the shopper is key to success for any marketing strategies that can optimize or personalize shopping-related services in real-time. We envision that exploiting the knowledge of real-time behavior of shopper’s in-store activities enables novel applications such as: (a) targeted advertising or recommendations: based on longer term shopper profiles, (b) proactive retail help to assist the shoppers who are confused in choosing between two items, (c) smart reminders that can remind …
Adaptable Key-Policy Attribute-Based Encryption With Time Interval, Siqi Ma, Junzuo Lai, Deng, Robert H., Xuhua Ding
Adaptable Key-Policy Attribute-Based Encryption With Time Interval, Siqi Ma, Junzuo Lai, Deng, Robert H., Xuhua Ding
Research Collection School Of Computing and Information Systems
In this paper, we introduce a new cryptographic primitive: adaptable KP-ABE with time interval (KP-TIABE), which is an extension of key-policy attribute-based encryption (KP-ABE). Adaptable KP-TIABE specifies a decryption time interval for every ciphertext such that the ciphertext can only be decrypted within this time interval. To be more flexible, the decryption time interval associated with a ciphertext can be adjusted on demand by a semi-trusted server. We propose a formal model for adaptable KP-TIABE, present a concrete adaptable KP-TIABE scheme and prove its security under the security model.
Value-Inspired Elderly Care Service Design For Aging-In-Place, Na Liu, Sandeep Purao, Hwee-Pink Tan
Value-Inspired Elderly Care Service Design For Aging-In-Place, Na Liu, Sandeep Purao, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Most current projects aimed at in-home monitoring for the elderly appear to focus on demonstrating technical feasibility and ensuring safety. In doing so, they often overlook the complexity of the interactions between the elderly and the caregivers. This study explores this complexity by adopting a value-inspired design perspective. Following an action design method, we describe the (re)design of the system and service protocol for an elderly-home monitoring effort. The work requires that we leverage the capabilities (of the technological infrastructure system as well as the service providers) to reconcile the values held by the participants (the elderly and their caregivers). …
Fusing Wifi And Video Sensing For Accurate Group Detection In Indoor Spaces, Kasthuri Jayarajah, Zaman Lantra, Archan Misra
Fusing Wifi And Video Sensing For Accurate Group Detection In Indoor Spaces, Kasthuri Jayarajah, Zaman Lantra, Archan Misra
Research Collection School Of Computing and Information Systems
Understanding one's group context in indoor spaces is useful for many reasons - e.g., at a shopping mall, knowing a customer's group context can help in offering context-specific incentives, or estimating taxi demand for customers exiting the mall. Group detection and monitoring using WiFi-based indoor location traces fails when users are invisible (either because they don't carry smartphones, or because their WiFi is turned OFF) or when location tracking is inaccurate. In this paper, we propose a multi-modal group detection system that fuses two independent modes: video and WiFi, for detecting groups with low latency and high accuracy. We present …
Indoor Location Error-Detection Via Crowdsourced Multi-Dimensional Mobile Data, Savina Singla, Archan Misra
Indoor Location Error-Detection Via Crowdsourced Multi-Dimensional Mobile Data, Savina Singla, Archan Misra
Research Collection School Of Computing and Information Systems
We explore the use of multi-dimensional mobile sensing data as a means of identifying errors in one or more of those data streams. More specifically, we look at the possibility of identifying indoor locations with likely incorrect/stale Wi-Fi fingerprints, by using concurrent readings from Wi-Fi and barometer sensors from a collection of mobile devices. Our key contribution is a novel two-step process: (i) using longitudinal, crowd-sourced readings of (possibly incorrect) Wi-Fi location estimates to statistically estimate the barometer calibration offset of individual mobile devices, and (ii) then, using such offset-corrected barometer readings from devices (that are supposedly collocated) to identify …
Cdrep: Automatic Repair Of Cryptographic-Misuses In Android Applications, Siqi Ma, David Lo, Teng Li, Robert H. Deng
Cdrep: Automatic Repair Of Cryptographic-Misuses In Android Applications, Siqi Ma, David Lo, Teng Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
Cryptography is increasingly being used in mobile applications to provide various security services; from user authentication, data privacy, to secure communications. However, there are plenty of mistakes that developers could accidentally make when using cryptography in their mobile apps and such mistakes can lead to a false sense of security. Recent research efforts indeed show that a significant portion of mobile apps in both Android and iOS platforms misused cryptographic APIs. In this paper, we present CDRep, a tool for automatically repairing cryptographic misuse defects in Android apps. We classify such defects into seven types and manually assemble the corresponding …
Leveraging Automated Privacy Checking For Design Of Mobile Privacy Protection Mechanisms, Joseph Joo Keng Chan, Lingxiao Jiang, Kiat Wee Tan, Rajesh Balan
Leveraging Automated Privacy Checking For Design Of Mobile Privacy Protection Mechanisms, Joseph Joo Keng Chan, Lingxiao Jiang, Kiat Wee Tan, Rajesh Balan
Research Collection School Of Computing and Information Systems
While mobile platforms rely on developers to follow good practices in privacy design, developers might not always adhere. In addition, it is often difficult for users to understand the privacy behaviour of their applications without some prolonged usage. To aid in these issues, we describe on-going research to improve privacy protection by utilizing techniques that mine privacy information from application binaries as a grey-box (Automated Privacy Checking). The outputs can then be utilized to improve the users' ability to exercise privacy-motivated discretion. We conducted a user study to observe the effects of presenting information on leak-causing triggers within applications in …
Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni
Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni
Research Collection School Of Computing and Information Systems
The Last Mile Problem (LMP) refers to the provision of travel service from the nearest public transportation node to a home or office. We study the supply side of this problem in a stochastic setting, with batch demands resulting from the arrival of groups of passengers who request last-mile service at urban rail stations or bus stops. Closedform approximations are derived for the performance of Last Mile Transportations Systems as a function of the fundamental design parameters of such systems. An initial set of results is obtained for the case in which a fleet of vehicles of unit capacity provides …
Reinforcement Learning Framework For Modeling Spatial Sequential Decisions Under Uncertainty: (Extended Abstract), Truc Viet Le, Siyuan Liu, Hoong Chuin Lau
Reinforcement Learning Framework For Modeling Spatial Sequential Decisions Under Uncertainty: (Extended Abstract), Truc Viet Le, Siyuan Liu, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We consider the problem of trajectory prediction, where a trajectory is an ordered sequence of location visits and corresponding timestamps. The problem arises when an agent makes sequential decisions to visit a set of spatial locations of interest. Each location bears a stochastic utility and the agent has a limited budget to spend. Given the agent's observed partial trajectory, our goal is to predict the remaining trajectory. We propose a solution framework to the problem considering both the uncertainty of utility and the budget constraint. We use reinforcement learning (RL) to model the underlying decision processes and inverse RL to …
Using Abstractions To Solve Opportunistic Crime Security Games At Scale, Chao Zhang, Victor Bucarey, Ayan Mukhopadhyay, Arunesh Sinha, Qian. Yundi, Yevgeniy Vorobeychik, Milind Tambe
Using Abstractions To Solve Opportunistic Crime Security Games At Scale, Chao Zhang, Victor Bucarey, Ayan Mukhopadhyay, Arunesh Sinha, Qian. Yundi, Yevgeniy Vorobeychik, Milind Tambe
Research Collection School Of Computing and Information Systems
In this paper, we aim to deter urban crime by recommending optimal police patrol strategies against opportunistic criminals in large scale urban problems. While previous work has tried to learn criminals' behavior from real world data and generate patrol strategies against opportunistic crimes, it cannot scale up to large-scale urban problems. Our first contribution is a game abstraction framework that can handle opportunistic crimes in large-scale urban areas. In this game abstraction framework, we model the interaction between officers and opportunistic criminals as a game with discrete targets. By merging similar targets, we obtain an abstract game with fewer total …
Fast Weighted Histograms For Bilateral Filtering And Nearest Neighbor Searching, Shengfeng He, Qingxiong Yang, Rynson W. H. Lau, Ming-Hsuan Yang
Fast Weighted Histograms For Bilateral Filtering And Nearest Neighbor Searching, Shengfeng He, Qingxiong Yang, Rynson W. H. Lau, Ming-Hsuan Yang
Research Collection School Of Computing and Information Systems
The locality sensitive histogram (LSH) injects spatial information into the local histogram in an efficient manner, and has been demonstrated to be very effective for visual tracking. In this paper, we explore the application of this efficient histogram in two important problems. We first extend the LSH to linear time bilateral filtering, and then propose a new type of histogram for efficiently computing edge-preserving nearest neighbor fields (NNFs). While the existing histogram-based bilateral filtering methods are the state of the art for efficient grayscale image processing, they are limited to box spatial filter kernels only. In our first application, we …
Optimizing Selection Of Competing Services With Probabilistic Hierarchical Refinement, Tian Huat Tan, Manman Chen, Jun Sun, Yang Liu, Étienne André, Yinxing Xue, Jin Song Dong
Optimizing Selection Of Competing Services With Probabilistic Hierarchical Refinement, Tian Huat Tan, Manman Chen, Jun Sun, Yang Liu, Étienne André, Yinxing Xue, Jin Song Dong
Research Collection School Of Computing and Information Systems
Recently, many large enterprises (e.g., Netflix, Amazon) have decomposed their monolithic application into services, and composed them to fulfill their business functionalities. Many hosting services on the cloud, with different Quality of Service (QoS) (e.g., availability, cost), can be used to host the services. This is an example of competing services. QoS is crucial for the satisfaction of users. It is important to choose a set of services that maximize the overall QoS, and satisfy all QoS requirements for the service composition. This problem, known as optimal service selection, is NPhard. Therefore, an effective method for reducing the search space …
You Are Being Watched: Bystanders' Perspective On The Use Of Camera Devices In Public Spaces, Samarth Singhal, Carman Neustaedter, Thecla Schiphorst, Anthony Tang, Abhisekh Patra, Rui Pan
You Are Being Watched: Bystanders' Perspective On The Use Of Camera Devices In Public Spaces, Samarth Singhal, Carman Neustaedter, Thecla Schiphorst, Anthony Tang, Abhisekh Patra, Rui Pan
Research Collection School Of Computing and Information Systems
We are observing an increase in the use of smartphones and wearable devices in public places for streaming and recording video. Yet the use of cameras in these devices can infringe upon the privacy of the people in the surrounding environment by inadvertently capturing them. This paper presents findings from an in-situ exploratory study that investigates bystanders' reactions and feelings towards streaming and recording videos with smartphones and wearable glasses in public spaces. We use the interview results to guide an exploration of design directions for mobile video.