Tze Ho Elden Tse

University of Birmingham, BAE Systems (United Kingdom)

Papers

Total Citations

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About

Tze Ho Elden Tse is a robotics researcher whose work bridges computer vision and auditory perception for autonomous systems. His primary research areas include 6D object pose tracking, sound-based speaker localization, and robust perception under challenging environmental conditions. Tse’s most cited work, "TP-AE: Temporally Primed 6D Object Pose Tracking with Auto-Encoders" (2022, 12 citations), introduces a novel framework that leverages temporal priors and auto-encoders to achieve fast, accurate tracking of symmetric and textureless objects—a critical capability for robotic manipulation in cluttered or occluded settings. This contribution directly addresses a long-standing challenge in instance-level pose tracking, enabling more reliable robot-environment interaction. In his earlier work, "No Need to Scream: Robust Sound-Based Speaker Localisation in Challenging Scenarios" (2019, 6 citations), Tse demonstrated innovative use of auditory cues for localization under adverse conditions, expanding the sensory toolkit for human-robot interaction. Together, these studies highlight Tse’s ability to combine temporal reasoning with multimodal sensing, producing practical solutions for real-world robotics. His research continues to influence the development of perception systems that are both resilient and computationally efficient.