Computer Sciences Commons^™

High-Speed Video From Asynchronous Camera Array, Si Lu

Computer Science Faculty Publications and Presentations

This paper presents a method for capturing high-speed video using an asynchronous camera array. Our method sequentially fires each sensor in a camera array with a small time offset and assembles captured frames into a high-speed video according to the time stamps. The resulting video, however, suffers from parallax jittering caused by the viewpoint difference among sensors in the camera array. To address this problem, we develop a dedicated novel view synthesis algorithm that transforms the video frames as if they were captured by a single reference sensor. Specifically, for any frame from a non-reference sensor, we find the two …

Recommender Systems Notation, Michael D. Ekstrand, Joseph A. Konstan

Computer Science Faculty Publications and Presentations

As the field of recommender systems has developed, authors have used a myriad of notations for describing the mathematical workings of recommendation algorithms. These notations appear in research papers, books, lecture notes, blog posts, and software documentation. The disciplinary diversity of the field has not contributed to consistency in notation; scholars whose home base is in information retrieval have different habits and expectations than those in machine learning or human-computer interaction.

In the course of years of teaching and research on recommender systems, we have seen the value in adopting a consistent notation across our work. This has been particularly …

Artificial Intelligence Hits The Barrier Of Meaning, Melanie Mitchell

Computer Science Faculty Publications and Presentations

Today’s AI systems sorely lack the essence of human intelligence: Understanding the situations we experience, being able to grasp their meaning. The lack of humanlike understanding in machines is underscored by recent studies demonstrating lack of robustness of state-of-the-art deep-learning systems. Deeper networks and larger datasets alone are not likely to unlock AI’s “barrier of meaning”; instead the field will need to embrace its original roots as an interdisciplinary science of intelligence.

Kidled: A Colorful Approach To Children's Activity Awareness, Ankita Samariya, Anud Sharma, Margiawan Fitriani, Tucker Ferguson, Jerry Alan Fails

Computer Science Faculty Publications and Presentations

Obesity in children is a growing cause of concern as it affects more than 18% of children in the United States. Sedentary behaviour is one of the contributors to childhood obesity. Technological interventions like activity trackers and fitness games have been introduced to motivate both children and adults to be physically active. Most of these technologies encourage activity by making them aware of their activity levels. While awareness of current activity levels may help motivating adults, it can be difficult for children to understand their activity levels in terms of number of steps (the most common method used by adults). …

Investigating The Social And Temporal Aspects Of Children’S Physical Activity Games, Ankita Samariya, Jerry Alan Fails, Derek Hansen

Computer Science Faculty Publications and Presentations

There are a variety of fitness technologies such as activity trackers, exergames and mobile applications available to promote physical activity. Based on our previous research, we found that children prefer having social interaction, a narrative and flexibility while interacting with such technologies. Other research has shown that persuasive displays encouraged adults towards physical activity. In this research, we present the initial results from a user study conducted on 16 children (ages 6-11) who used the Kidfit suite, a collection of mobile applications that combine and utilize the elements found from previous research to promote activity in children.

Predicting Human Interpretations Of Affect And Valence In A Social Robot, David Mcneill, Casey Kennington

Computer Science Faculty Publications and Presentations

In this paper we seek to understand how people interpret a social robot’s performance of an emotion, what we term ‘affective display,’ and the positive or negative valence of that affect. To this end, we tasked annotators with observing the Anki Cozmo robot perform its over 900 pre-scripted behaviors and labeling those behaviors with 16 possible affective display labels (e.g., interest, boredom, disgust, etc.). In our first experiment, we trained a neural network to predict annotated labels given multimodal information about the robot’s movement, face, and audio. The results suggest that pairing affects to predict the valence between them is …

High-Speed Video From Asynchronous Camera Array (Poster), Si Lu

Computer Science Faculty Publications and Presentations

Poster presented at: 2019 IEEE Winter Conference on Applications of Computer Vision (WACV)

Good Similar Patches For Image Denoising (Poster), Si Lu

Computer Science Faculty Publications and Presentations

Patch-based denoising algorithms like BM3D have achieved outstanding performance. An important idea for the success of these methods is to exploit the recurrence of similar patches in an input image to estimate the underlying image structures....

Context-Aware Synthesis For Video Frame Interpolation, Simon Niklaus, Feng Liu

Computer Science Faculty Publications and Presentations

Video frame interpolation algorithms typically estimate optical flow or its variations and then use it to guide the synthesis of an intermediate frame between two consecutive original frames. To handle challenges like occlusion, bidirectional flow between the two input frames is often estimated and used to warp and blend the input frames. However, how to effectively blend the two warped frames still remains a challenging problem. This paper presents a context-aware synthesis approach that warps not only the input frames but also their pixel-wise contextual information and uses them to interpolate a high-quality intermediate frame. Specifically, we first use a …

Panel: Broadening The Discussion Of Ethics In The Interaction Design And Children Community, Christopher Frauenberger, Monica Landoni, Jerry Alan Fails, Janet C. Read, Alissa N. Antle, Pauline Gourlet

Computer Science Faculty Publications and Presentations

Interaction Design and Children (IDC) as an academic field, and as a community, has a responsibility to engage with the many and diverse ethical challenges that arise from work that concerns the creation of digital technology for and with children – both in terms of research and industry contexts. This panel builds on a short history of similar events at previous conferences and aims to foster and strengthen the debate about ethical conduct and moral responsibilities in IDC. In this year’s panel, we seek to broaden the discussion by collecting ethical concerns, issues or dilemmas from within the community to …

The Seven Layers Of Complexity Of Recommender Systems For Children In Educational Contexts, Emiliana Murgia, Monica Landoni, Theo Huibers, Jerry Alan Fails, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

Recommender systems (RS) in their majority focus on an average target user: adults. We argue that for non-traditional populations in specific contexts, the task is not as straightforward–we must look beyond existing recommendation algorithms, premises for interface design, and standard evaluation metrics and frameworks. We explore the complexity of RS in an educational context for which young children are the target audience. The aim of this position paper is to spell out, label, and organize the specific layers of complexity observed in this context.

“My Name Is My Password:” Understanding Children’S Authentication Practices, Dhanush Kumar Ratakonda, Tyler French, Jerry Alan Fails

Computer Science Faculty Publications and Presentations

Children continue to use technology at an increasing rate, more and more of which require authentication via usernames and passwords.We seek to understand how children ages 5-11 years old create and use their credentials. We investigate children’s username and password understanding and practices from the perspective of both children and adults within the context of three security categories: credential composition (e.g. length of password), performance (e.g. time to enter), and credential mechanisms (e.g; a pattern or characters). We conducted a semi-structured interview with 22 children and an online survey with 33 adult participants (parents and teachers) to determine their practices …

Pushing The Boundaries Of Participatory Design With Children With Special Needs, Jerry Alan Fails

Computer Science Faculty Publications and Presentations

Despite its inherent challenges, participatory design (PD) has unique benefits when designing technology for children, especially children with special needs. Researchers have developed a multitude of PD approaches to accommodate specific populations. However, a lack of understanding of the appropriateness of existing approaches across contexts presents a challenge for PD researchers. This workshop will provide an opportunity for PD researchers to exchange and reflect on their experiences of designing with children with special needs. We aim to identify, synthesize and collate PD best practices across contexts and participant groups.

3Rd Kidrec Workshop: What Does Good Look Like?, Theo Huibers, Jerry Alan Fails, Natalia Kucirkova, Monica Landoni, Emiliana Murgia, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

Today’s children spend considerable time online, searching and receiving information from various websites and apps. While searching for information, e.g. for school or hobbies, children use search systems to locate resources and receive site recommendations that might be useful for them. The call for good, reliable, child-friendly systems has been made many times and the thesis that the algorithms of “adult” information systems are not necessarily suitable or fair for children is widely accepted. However, there is still no clear and balanced view on what makes one search/recommendation system for children good or better than other systems, nor on what …

"Anon What What?": Children's Understanding Of The Language Of Privacy, Stacy Black, Rezvan Joshaghani, Dhanush Kumar Ratakonda, Hoda Mehrpouyan, Jerry Alan Fails

Computer Science Faculty Publications and Presentations

Internet usage continues to increase among children ages 12 and younger. Because their digital interactions can be persistently stored, there is a need for building an understanding and foundational knowledge of privacy. We describe initial investigations into children’s understanding of privacy from a Contextual Integrity (CI) perspective by conducting semi-structured interviews. We share results – that echo what others have shown – that indicate children have limited knowledge and understanding of CI principles. We also share an initial exploration of utilizing participatory design theater as a possible educational mechanism to help children develop a stronger understanding of important privacy principles.

With A Little Help From My Friends: Use Of Recommendations At School, Maria Soledad Pera, Emiliana Murgia, Monica Landoni, Theo Huibers

Computer Science Faculty Publications and Presentations

In this exploratory paper, we study the usage of recommendations by and for children (ages 9 to 11) in an educational setting. From our preliminary analysis, it becomes apparent that recommender systems (RS) could provide extra support to and help children successfully complete inquiry tasks. Nonetheless, children have difficulty in recognizing the role of RS, in terms of aiding information discovery for classroom assignments. Findings from our study set a foundation that can inform future design and development of RS for children that support classroom-related work.

Fairness And Discrimination In Recommendation And Retrieval, Michael D. Ekstrand, Robin Burke, Fernando Diaz

Computer Science Faculty Publications and Presentations

Fairness and related concerns have become of increasing importance in a variety of AI and machine learning contexts. They are also highly relevant to recommender systems and related problems such as information retrieval, as evidenced by the growing literature in RecSys, FAT*, SIGIR, and special sessions such as the FATREC and FACTS-IR workshops and the Fairness track at TREC 2019; however, translating algorithmic fairness constructs from classification, scoring, and even many ranking settings into recommendation and other information access scenarios is not a straightforward task. This tutorial will help orient RecSys researchers to algorithmic fairness, understand how concepts do and …

Here, There, And Everywhere: Building A Scaffolding For Children’S Learning Through Recommendations, Ashlee Milton, Emiliana Murgia, Monica Landoni, Theo Huibers, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

Reading and literacy are on the decline among children. This is compounded by the fact that children have trouble with the discovery of resources that are appropriate, diverse, and appealing. With technology becoming an evermore presence in children’s lives, tools that can minimize choice overload and ease access to online resources become a must. A powerful but underutilized tool in regards to children that could assist in this situation is a recommender system (RS). We posit that RS could be used to impact children’s learning, using them to not only suggest what children might like but what they need in …

Joint Stabilization And Direction Of 360° Videos, Chengzhou Tang, Oliver Wang, Feng Liu, Ping Tan

Computer Science Faculty Publications and Presentations

Three-hundred-sixty-degree (360°) video provides an immersive experience for viewers, allowing them to freely explore the world by turning their head. However, creating high-quality 360° video content can be challenging, as viewers may miss important events by looking in the wrong direction, or they may see things that ruin the immersion, such as stitching artifacts and the film crew. We take advantage of the fact that not all directions are equally likely to be observed; most viewers are more likely to see content located at “true north,” i.e., in front of them, due to ergonomic constraints. We therefore propose 360° video …

Samu: Design And Implementation Of Frequency Selectivity-Aware Multi-User Mimo For Wlans, Yongjiu Du, Yan Shi, Ehsan Aryafar, Pengfei Cui, Joseph Camp, Mung Chiang

Computer Science Faculty Publications and Presentations

The traffic demand of wireless networks is expected to increase 1000-fold over the next decade. In anticipation of such increasing data demand for dense networks with a large number of stations, IEEE 802.11ax has introduced key technologies for capacity improvement including Orthogonal Frequency-Division Multiple Access (OFDMA), multi-user multi-input multi-output (MU-MIMO), and greater bandwidth. However, IEEE 802.11ax has yet to fully define a specific scheduling framework, on which the throughput improvement of networks significantly depends. Even within a 20 MHz of bandwidth, users experience heterogeneous channel orthogonality characteristics across sub-carriers, which prevents access points (APs) from achieving the ideal multi-user gain. …

Child-Computer Interaction, Ubiquitous Technologies, And Big Data, Jerry Alan Fails

Computer Science Faculty Publications and Presentations

The children's technology landscape is changing quickly. The ubiquity of interactive technologies means children can access them just about anytime, anywhere. At the same time, these technologies constantly collect data from and about children, bringing them into the age of big data, voluntarily or not. These developments have the potential to significantly change children's relationship to technology and the long-term impact of technology use. To discuss these changes, the child-computer-interaction community held a special interest group (SIG) meeting during the CHI 2018 conference.

A New Functional-Logic Compiler For Curry: Sprite, Sergio Antoy, Andy Jost

Computer Science Faculty Publications and Presentations

We introduce a new native code compiler for Curry codenamed Sprite. Sprite is based on the Fair Scheme, a compilation strategy that provides instructions for transforming declarative, non-deterministic programs of a certain class into imperative, deterministic code. We outline salient features of Sprite, discuss its implementation of Curry programs, and present benchmarking results. Sprite is the first-to-date operationally complete implementation of Curry. Preliminary results show that ensuring this property does not incur a significant penalty.

A Cyber-Physical System Framework For Early Detection Of Paroxysmal Diseases, Zuxing Gu, Yu Jiang, Min Zhou, Xiaoyu Song, Lui Sha

Computer Science Faculty Publications and Presentations

Paroxysmal diseases of inpatients are globally recognized as one of the top challenges in medicine. Poor clinical outcomes are primarily caused by delayed recognition, especially due to diverse clinical diagnostic criteria with complex manifestations, irregular episodes, and already overloaded clinical activities. With the proliferation of measuring devices and increased computational capabilities, cyber-physical characterization plays an increasingly important role in many domains to provide enabling technologies. This paper presents a cyber-physical system (CPS) framework to assist physicians in making earlier diagnoses of paroxysmal sympathetic hyperactivity based on existing medical knowledge. We propose a configurable diagnostic knowledge model to characterize clinical criteria …

A Shoulder Surfing Resistant Graphical Authentication System, Hung-Min Sun, Shiuan-Tung Chen, Jyh-Haw Yeh, Chia-Yun Cheng

Computer Science Faculty Publications and Presentations

Authentication based on passwords is used largely in applications for computer security and privacy. However, human actions such as choosing bad passwords and inputting passwords in an insecure way are regarded as ”the weakest link” in the authentication chain. Rather than arbitrary alphanumeric strings, users tend to choose passwords either short or meaningful for easy memorization. With web applications and mobile apps piling up, people can access these applications anytime and anywhere with various devices. This evolution brings great convenience but also increases the probability of exposing passwords to shoulder surfing attacks. Attackers can observe directly or use external recording …

When Good Components Go Bad: Formally Secure Compilation Despite Dynamic Compromise, Guglielmo Fachini, CăTăLin Hriţcu, Marco Stronati, Arthur Azevedo De Amorim, Carmine Abate, Roberto Blanco, Théo Laurent, Benjamin C. Pierce, Andrew Tolmach

Computer Science Faculty Publications and Presentations

We propose a new formal criterion for secure compilation, giving strong end-to-end security guarantees for software components written in unsafe, low-level languages with C-style undefined behavior. Our criterion is the first to model dynamic compromise in a system of mutually distrustful components running with least privilege. Each component is protected from all the others—in particular, from components that have encountered undefined behavior and become compromised. Each component receives secure compilation guarantees up to the point when it becomes compromised, after which an attacker can take complete control over the component and use any of its privileges to attack the remaining …

Investigating Query Formulation Assistance For Children, Oghenemaro Anuyah, Maria Soledad Pera, Jerry Alan Fails

Computer Science Faculty Publications and Presentations

Popular tools used to search for online resources are tuned to satisfy a broad category of users—primarily adults. Because children have specific needs, these tools may not always be successful in offering the right level of support in their quest for information. While search tools often provide query assistance, children still face many difficulties expressing their information needs in the form of a query. In this paper, we share results from our ongoing research work focused on understanding children's interactions with query suggestions and their preferences with respect to suggestions offered by a general-purpose strategy versus a counterpart designed exclusively …

Exploring Author Gender In Book Rating And Recommendation, Michael D. Ekstrand, Mucun Tian, Mohammed R. Imran Kazi, Hoda Mehrpouyan, Daniel Kluver

Computer Science Faculty Publications and Presentations

Collaborative filtering algorithms find useful patterns in rating and consumption data and exploit these patterns to guide users to good items. Many of the patterns in rating datasets reflect important real-world differences between the various users and items in the data; other patterns may be irrelevant or possibly undesirable for social or ethical reasons, particularly if they reflect undesired discrimination, such as gender or ethnic discrimination in publishing. In this work, we examine the response of collaborative filtering recommender algorithms to the distribution of their input data with respect to a dimension of social concern, namely content creator gender. Using …

International And Interdisciplinary Perspectives On Children & Recommender Systems (Kidrec), Jerry Alan Fails, Maria Soledad Pera, Natalia Kucirkova, Franca Garzotto

Computer Science Faculty Publications and Presentations

Resources for children are abundant, but finding suitable and appropriate resources for children in our information-rich society can be challenging. Due to this abundance of information, systems to find and recommend appropriate information for children are needed. Recommender systems (RS) for children have only recently begun to be researched. This area of research brings together researchers in education, child-development, computer scientists, designers, and more who address several issues including those related to education, algorithms, ethics, privacy, security. In this workshop we will: discuss and identify issues related to RS designed for children including challenges and limitations, discuss possible solutions to …

Structurally Defined Conditional Data-Flow Static Analysis, Elena Sherman, Matthew B. Dwyer

Computer Science Faculty Publications and Presentations

Data flow analysis (DFA) is an important verification technique that computes the effect of data values propagating over program paths. While more precise than flow-insensitive analyses, such an analysis is time-consuming.

This paper investigates the acceleration of DFA by structural decomposition of the underlying control flow graph. Specifically, we explore the cost and effectiveness of dividing program paths into subsets by partitioning path suffixes at conditional statements, applying a DFA on each subset, and then combining the resulting invariants. This yields a family of independent DFA problems that are solved in parallel and where the partial results of each problem …

The Lkpy Package For Recommender Systems Experiments, Michael D. Ekstrand

Computer Science Faculty Publications and Presentations

Since 2010, we have built and maintained LensKit, an open-source toolkit for building, researching, and learning about recommender systems. We have successfully used the software in a wide range of recommender systems experiments, to support education in traditional classroom and online settings, and as the algorithmic backend for user-facing recommendation services in movies and books. This experience, along with community feedback, has surfaced a number of challenges with LensKit’s design and environmental choices. In response to these challenges, we are developing a new set of tools that leverage the PyData stack to enable the kinds of research experiments and educational …