TY - GEN
T1 - Laplacian vision
T2 - 7th Augmented Human International Conference, AH 2016
AU - Itoh, Yuta
AU - Orlosky, Jason
AU - Kiyokawa, Kiyoshi
AU - Klinker, Gudrun
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/2/25
Y1 - 2016/2/25
N2 - Nave physics [7], or folk physics, is our ability to understand physical phenomena. We regularly use this ability in life to avoid collisions in trafic, follow a tennis ball and time the return shot, or while working in dynamic industrial settings. Though this skill improves with practice, it is still imperfect, which leads to mistakes and misjudgments for time intensive tasks. People still often miss a tennis shot, which might cause them to lose the match, or fail to avoid a car or pedestrian, which can lead to injury or even death. As a step towards reducing these errors in human judgement, we present Laplacian Vision (LV), a vision augmentation system which assists the human ability to predict future trajectory information. By tracking real world objects and estimating their trajectories, we can improve a users's prediction of the landing spot of a ball or the path of an oncoming car. We have designed a system that can track a ying ball in real time, predict its future trajectory, and visualize it in the user's field of view. The system is also calibrated to account for end- To-end delays so that the trajectory appears to emanate forward from the moving object. We also conduct a user study where 29 subjects predict an object's landing spot, and show that prediction accuracy improves 3 fold using LV.
AB - Nave physics [7], or folk physics, is our ability to understand physical phenomena. We regularly use this ability in life to avoid collisions in trafic, follow a tennis ball and time the return shot, or while working in dynamic industrial settings. Though this skill improves with practice, it is still imperfect, which leads to mistakes and misjudgments for time intensive tasks. People still often miss a tennis shot, which might cause them to lose the match, or fail to avoid a car or pedestrian, which can lead to injury or even death. As a step towards reducing these errors in human judgement, we present Laplacian Vision (LV), a vision augmentation system which assists the human ability to predict future trajectory information. By tracking real world objects and estimating their trajectories, we can improve a users's prediction of the landing spot of a ball or the path of an oncoming car. We have designed a system that can track a ying ball in real time, predict its future trajectory, and visualize it in the user's field of view. The system is also calibrated to account for end- To-end delays so that the trajectory appears to emanate forward from the moving object. We also conduct a user study where 29 subjects predict an object's landing spot, and show that prediction accuracy improves 3 fold using LV.
KW - Augmented reality
KW - HMD
KW - Prediction
KW - Tracking
KW - Vision augmentation
UR - http://www.scopus.com/inward/record.url?scp=84985911657&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84985911657&partnerID=8YFLogxK
U2 - 10.1145/2875194.2875227
DO - 10.1145/2875194.2875227
M3 - Conference contribution
AN - SCOPUS:84985911657
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 7th Augmented Human International Conference, AH 2016
PB - Association for Computing Machinery
Y2 - 25 February 2016 through 27 February 2016
ER -