17 citations · 56 across the 13 of their papers we have counts for
13 papers
D3D-GEN: Robot-Aware Domain-Grounded Interactive 3D World Generation for Social Robotics
Anh Duc Do, Volodymyr Shcherbyna, Tai Duc Nguyen +5
Training and validation of Embodied AI for social navigation critically depends on realistic simulation environments, yet many current approaches fail to find a balance between rea…
Empath-D: VR-based Empathetic App Design for Accessibility
Wonjung Kim, Kenny Tsu Wei Choo, Youngki Lee +2
With app-based interaction increasingly permeating all aspects of daily living, it is essential to ensure that apps are designed to be \emph{inclusive} and are usable by a wider au…
MOSAIC: Spatially-Multiplexed Edge AI Optimization over Multiple Concurrent Video Sensing Streams
Ila Gokarn, Hemanth Sabella, Yigong Hu +2
Sustaining high fidelity and high throughput of perception tasks over vision sensor streams on edge devices remains a formidable challenge, especially given the continuing increase…
Demo: RhythmEdge: Enabling Contactless Heart Rate Estimation on the Edge
Zahid Hasan, Emon Dey, Sreenivasan Ramasamy Ramamurthy +2
In this demo paper, we design and prototype RhythmEdge, a low-cost, deep-learning-based contact-less system for regular HR monitoring applications. RhythmEdge benefits over existin…
DeepLight: Robust & Unobtrusive Real-time Screen-Camera Communication for Real-World Displays
Vu Tran, Gihan Jayatilaka, Ashwin Ashok +1
The paper introduces a novel, holistic approach for robust Screen-Camera Communication (SCC), where video content on a screen is visually encoded in a human-imperceptible fashion a…
Experiences & Challenges with Server-Side WiFi Indoor Localization Using Existing Infrastructure
Dheryta Jaisinghani, Vinayak Naik, Rajesh Balan +2
Real-world deployments of WiFi-based indoor localization in large public venues are few and far between as most state-of-the-art solutions require either client or infrastructure-s…
Enabling Collaborative Video Sensing at the Edge through Convolutional Sharing
Kasthuri Jayarajah, Dhanuja Wanniarachchige, Archan Misra
While Deep Neural Network (DNN) models have provided remarkable advances in machine vision capabilities, their high computational complexity and model sizes present a formidable ro…
Jointly Optimizing Sensing Pipelines for Multimodal Mixed Reality Interaction
Darshana Rathnayake, Ashen de Silva, Dasun Puwakdandawa +3
Natural human interactions for Mixed Reality Applications are overwhelmingly multimodal: humans communicate intent and instructions via a combination of visual, aural and gestural…
Inferring Accurate Bus Trajectories from Noisy Estimated Arrival Time Records
Lakmal Meegahapola, Noel Athaide, Kasthuri Jayarajah +2
Urban commuting data has long been a vital source of understanding population mobility behaviour and has been widely adopted for various applications such as transport infrastructu…
Prior Activation Distribution (PAD): A Versatile Representation to Utilize DNN Hidden Units
Lakmal Meegahapola, Vengateswaran Subramaniam, Lance Kaplan +1
In this paper, we introduce the concept of Prior Activation Distribution (PAD) as a versatile and general technique to capture the typical activation patterns of hidden layer units…
BuSCOPE : Fusing Individual & Aggregated Mobility Behavior for "Live" Smart City Services
Lakmal Meegahapola, Thivya Kandappu, Kasthuri Jayarajah +3
While analysis of urban commuting data has a long and demonstrated history of providing useful insights into human mobility behavior, such analysis has been performed largely in of…
Can multimodal sensing detect and localize transient events?
Kasthuri Jayarajah, Vigneshwaran Subbaraju, Noel Athaide +3
With the increased focus on making cities "smarter", we see an upsurge in investment in sensing technologies embedded in the urban infrastructure. The deployment of GPS sensors abo…
BreathRNNet: Breathing Based Authentication on Resource-Constrained IoT Devices using RNNs
Jagmohan Chauhan, Suranga Seneviratne, Yining Hu +3
Recurrent neural networks (RNNs) have shown promising results in audio and speech processing applications due to their strong capabilities in modelling sequential data. In many app…