Abstract: Event cameras are bio-inspired sensors that capture intensity changes of pixels individually, and generate asynchronous and independent ``events’’. Due to the fundamental difference from the conventional cameras, most research on event cameras builds a global event frame by...
Abstract: This paper proposes the object depth estimation in real-time, using only a monocular camera in an onboard computer with a low-cost GPU. Our algorithm estimates scene depth from a sparse feature-based visual odometry algorithm and detects/tracks objects’ bounding box by util...
Abstract: In the paper, we propose a robust real-time visual odometry in dynamic environments via rigid-motion model updated by scene flow. The proposed algorithm consists of spatial motion segmentation and temporal motion tracking. The spatial segmentation first generates several mo...
Abstract: In this work, we propose an edge detection algorithm by estimating a lifetime of an event produced from dynamic vision sensor, also known as event camera. The event camera, unlike traditional CMOS camera, generates sparse event data at a pixel whose log-intensity changes. D...
Abstract: This paper proposes an edge-based robust RGB-D visual odometry (VO) using 2-D edge divergence minimization. Our approach focuses on enabling the VO to operate in more general environments subject to low texture and changing brightness, by employing image edge regions and th...