81 citations · 89 across the 7 of their papers we have counts for
7 papers
Negotiating Ontological Boundaries in User-Authored Personal Sensing Systems
Nava Haghighi, Danielle Olson, Halden Lin +4
Designed artifacts are ontological, shaping, and at times limiting, what becomes possible or imaginable. One path toward mitigating such foreclosures is giving people power over ho…
SlotFM: A Motion Foundation Model with Slot Attention for Diverse Downstream Tasks
Junyong Park, Oron Levy, Rebecca Adaimi +3
Wearable accelerometers are used for a wide range of applications, such as gesture recognition, gait analysis, and sports monitoring. Yet most existing foundation models focus prim…
Towards AI-driven Sign Language Generation with Non-manual Markers
Han Zhang, Rotem Shalev-Arkushin, Vasileios Baltatzis +7
Sign languages are essential for the Deaf and Hard-of-Hearing (DHH) community. Sign language generation systems have the potential to support communication by translating from writ…
Moonwalk: Advancing Gait-Based User Recognition on Wearable Devices with Metric Learning
Asaf Liberman, Oron Levy, Soroush Shahi +5
Personal devices have adopted diverse authentication methods, including biometric recognition and passcodes. In contrast, headphones have limited input mechanisms, depending solely…
Advancing Location-Invariant and Device-Agnostic Motion Activity Recognition on Wearable Devices
Rebecca Adaimi, Abdelkareem Bedri, Jun Gong +5
Wearable sensors have permeated into people's lives, ushering impactful applications in interactive systems and activity recognition. However, practitioners face significant obstac…
Vision-Based Hand Gesture Customization from a Single Demonstration
Soroush Shahi, Vimal Mollyn, Cori Tymoszek Park +6
Hand gesture recognition is becoming a more prevalent mode of human-computer interaction, especially as cameras proliferate across everyday devices. Despite continued progress in t…
Enabling hand gesture customization on wrist-worn devices
Xuhai Xu, Jun Gong, Carolina Brum +13
We present a framework for gesture customization requiring minimal examples from users, all without degrading the performance of existing gesture sets. To achieve this, we first de…