Hybrid Indirect-Direct Visual SLAM for Embedded Platforms
Developed a hybrid indirect-direct monocular visual Simultaneous Localization and Mapping (SLAM) system for embedded and resource-constrained platforms. The work combines feature-based tracking, direct photometric alignment, and OpenGL ES compute-shader acceleration to improve real-time performance on commodity GPU-equipped devices.
Bayesian Multi-Object Tracking for ADAS
Developed a Kalman-filter-based Bayesian Multi-Object Tracking (MOT) module for an Advanced Driver Assistance Systems (ADAS) LiDAR perception pipeline. The work included real-time tracking, data association, integration, and testing under operational constraints, and was later extended toward radar-based and defense-related perception applications.
Early VR SLAM Prototyping
An early prototyping stage of the work that later became Mesh2SLAM in VR, a fast geometry-based SLAM framework for rapid prototyping in virtual reality applications. This project focused on building and testing the core tracking and mapping pipeline in C++ and OpenGL from the ground up, including early GPU compute-shader experiments for SLAM acceleration.
Simulation and Training Systems
Developed VR-based simulation and training software for defense applications using real-time 3D engines. Due to NDA constraints, project details are limited, but the work involved real-time 3D training applications, custom interaction logic, and simulation behavior. I also contributed to experimental camera calibration, camera–LiDAR fusion, and 3D mapping work.
Invention: Pinch/Grab (2011–2013)
While at Softkinetic Systems, I co-invented and helped develop the pinch/grab interaction concept for depth and RGB-D camera systems. This work was later patented and became a widely adopted interaction paradigm in VR, AR, and smart glasses.