Designing to Support Workspace Awareness in Remote Collaboration using 2D Interactive Surfaces

Increasing distributions of the global workforce are leading to collaborative workamong remote coworkers. The emergence of such remote collaborations is essentiallysupported by technology advancements of screen-based devices ranging from tabletor laptop to large displays. However, these devices, especially personal and mobilecomputers, still suffer from certain limitations caused by their form factors, that hinder supporting workspace awareness through non-verbal communication suchas bodily gestures or gaze. This thesis thus aims to design novel interfaces andinteraction techniques to improve remote coworkers’ workspace awareness throughsuch non-verbal cues using 2D interactive surfaces.The thesis starts off by exploring how visual cues support workspace awareness infacilitated brainstorming of hybrid teams of co-located and remote coworkers. Basedon insights from this exploration, the thesis introduces three interfaces for mobiledevices that help users maintain and convey their workspace awareness with their coworkers. The first interface is a virtual environment that allows a remote person to effectively maintain his/her awareness of his/her co-located collaborators’ activities while interacting with the shared workspace. To help a person better express his/her hand gestures in remote collaboration using a mobile device, the second interfacepresents a lightweight add-on for capturing hand images on and above the device’sscreen; and overlaying them on collaborators’ device to improve their workspace awareness. The third interface strategically leverages the entire screen space of aconventional laptop to better convey a remote person’s gaze to his/her co-locatedcollaborators. Building on the top of these three interfaces, the thesis envisions an interface that supports a person using a mobile device to effectively collaborate with remote coworkers working with a large display.Together, these interfaces demonstrate the possibilities to innovate on commodity devices to offer richer non-verbal communication and better support workspace awareness in remote collaboration

Specification and Verification of Shared-Memory Concurrent Programs

Ph.DDOCTOR OF PHILOSOPH

An Inertial Block Majorization Minimization Framework for Nonsmooth Nonconvex Optimization

In this paper, we introduce TITAN, a novel inerTIal block majorizaTion minimizAtioN framework for non-smooth non-convex optimization problems. To the best of our knowledge, TITAN is the first framework of block-coordinate update method that relies on the majorization-minimization framework while embedding inertial force to each step of the block updates. The inertial force is obtained via an extrapolation operator that subsumes heavy-ball and Nesterov-type accelerations for block proximal gradient methods as special cases. By choosing various surrogate functions, such as proximal, Lipschitz gradient, Bregman, quadratic, and composite surrogate functions, and by varying the extrapolation operator, TITAN produces a rich set of inertial block-coordinate update methods. We study sub-sequential convergence as well as global convergence for the generated sequence of TITAN. We illustrate the effectiveness of TITAN on two important machine learning problems, namely sparse non-negative matrix factorization and matrix completion.Comment: 32 page

HybridMingler: Towards Mixed-Reality Support for Mingling at Hybrid Conferences

Mingling, the activity of ad-hoc, private, opportunistic conversations ahead of, during, or after breaks, is an important socializing activity for attendees at scheduled events, such as in-person conferences. The Covid-19 pandemic had a dramatic impact on the way conferences are organized, so that most of them now take place in a hybrid mode where people can either attend on-site or remotely. While on-site attendees can resume in-person mingling, hybrid modes make it challenging for remote attendees to mingle with on-site peers. In addressing this problem, we propose a collaborative mixed-reality (MR) concept, including a prototype, called HybridMingler. This is a distributed MR system supporting ambient awareness and allowing both on-site and remote conference attendees to virtually mingle. HybridMingler aims to provide both on-site and remote attendees with a spatial sense of co-location in the very same venue location, thus ultimately improving perceived presence

Performance of DASH over Multipath TCP

Recently, dynamic adaptive streaming over HTTP (DASH) is a dominated traffic in Internet. The client requests a suitable representation depending on the current network condition. On the other hand, multipath transmission control protocols emerges as potential data transmission utilizing multiple network paths concurrently. In this paper, we conduct extensively experiments to evaluate the performance of DASH over MPTCP. Four different performance metrics are investigated, i.e., time on high quality, impactful switches, switch frequency, and average bitrate. The results show that the performance of DASH decreases when the paths of MPTCP have different bandwidths

MirrorNet: Bio-Inspired Camouflaged Object Segmentation

Camouflaged objects are generally difficult to be detected in their natural environment even for human beings. In this paper, we propose a novel bio-inspired network, named the MirrorNet, that leverages both instance segmentation and mirror stream for the camouflaged object segmentation. Differently from existing networks for segmentation, our proposed network possesses two segmentation streams: the main stream and the mirror stream corresponding with the original image and its flipped image, respectively. The output from the mirror stream is then fused into the main stream's result for the final camouflage map to boost up the segmentation accuracy. Extensive experiments conducted on the public CAMO dataset demonstrate the effectiveness of our proposed network. Our proposed method achieves 89% in accuracy, outperforming the state-of-the-arts. Project Page: https://sites.google.com/view/ltnghia/research/camoComment: Under Revie