Papers
4
Total Citations
574
H-Index
4
About
Betty J. Mohler is a leading researcher at the intersection of human perception, virtual reality, and human-robot interaction. Her work fundamentally explores how humans perceive self-motion, body ownership, and learn in immersive environments. A cornerstone of her impact is the highly cited paper "Recording and Playback of Camera Shake" (435 citations), which provided a real-world benchmark dataset that advanced the field of blind deconvolution in image processing. In perception science, she developed a novel continuous pointing method to measure instantaneous perceived self-motion during passive translations (45 citations), offering a high-resolution tool to quantify how we experience movement in space. Mohler has also bridged cognitive science and robotics, notably in "How Cognitive Models of Human Body Experience Might Push Robotics" (24 citations), arguing that Bayesian models of multisensory integration can guide the design of more intuitive assistive devices. Her interdisciplinary approach extends to learning, as seen in her work on inverse reinforcement learning for table tennis (70 citations). Through these contributions, Mohler has shaped our understanding of embodied perception and its applications in VR and robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Learning strategies in table tennis using inverse reinforcement learning70 citations · 2014
- 3Measurement of instantaneous perceived self-motion using continuous pointing45 citations · 2009
- 4How Cognitive Models of Human Body Experience Might Push Robotics24 citations · 2019