Christopher Ham

Australian Centre for Robotic Vision, Carnegie Mellon University

Papers

Total Citations

H-Index

About

Christopher Ham’s research focuses on the intersection of computer vision, 3D reconstruction, and mobile sensing, with a particular emphasis on scale estimation in monocular vision systems. His most cited work, “Hand Waving Away Scale” (2014, 12 citations), introduces a novel approach to inferring absolute scale from single-camera input, challenging conventional reliance on stereo or depth sensors. This contribution is foundational for applications in augmented reality and robotics on resource-constrained platforms. Expanding on this, his 2015 paper “Absolute Scale Estimation of 3D Monocular Vision on Smart Devices” (3 citations) demonstrates practical implementation on smartphones, bridging theoretical advances with real-world deployment. Though his citation counts are modest, Ham’s work is notable for its conceptual clarity and direct relevance to emerging mobile vision technologies. His research addresses a critical bottleneck in monocular SLAM systems, offering lightweight solutions that do not require additional hardware. For students and researchers exploring efficient 3D perception, Ham’s contributions provide a clear entry point into the challenges and innovations of scale-aware vision on everyday devices.