TY - GEN
T1 - Towards a disambiguation canvas
AU - Oebarba, Henrique G.
AU - Grandi, Jeronimo
AU - Maciel, Anderson
AU - Nedel, Luciana
AU - Boulic, Ronan
PY - 2013
Y1 - 2013
N2 - We present Disambiguation canvas, a technique for selection by progressive refinement using a mobile device and consisting of two steps. During the first, the user defines a subset of objects through the orientation sensors of the device and a volume-casting pointing technique. The subsequent step consists of the disambiguation of the desired target among the previously-defined subset of objects, and is accomplished using the mobile device touchscreen. By relying on the touchscreen for the last step the user can disambiguate among hundreds of objects at once, previous progressive refinement techniques do not scale as well as ours. Disambiguation canvas is mainly developed for easy, accurate and fast selection of small objects, or objects inside cluttered virtual environments. User tests show that our technique performs faster than ray-casting for targets with ≈ 0.53° of angular size, and is also much more accurate for all the tested target sizes.
AB - We present Disambiguation canvas, a technique for selection by progressive refinement using a mobile device and consisting of two steps. During the first, the user defines a subset of objects through the orientation sensors of the device and a volume-casting pointing technique. The subsequent step consists of the disambiguation of the desired target among the previously-defined subset of objects, and is accomplished using the mobile device touchscreen. By relying on the touchscreen for the last step the user can disambiguate among hundreds of objects at once, previous progressive refinement techniques do not scale as well as ours. Disambiguation canvas is mainly developed for easy, accurate and fast selection of small objects, or objects inside cluttered virtual environments. User tests show that our technique performs faster than ray-casting for targets with ≈ 0.53° of angular size, and is also much more accurate for all the tested target sizes.
KW - H.5.2 [User Interfaces]: Input devices and strategies (e.g mouse, touchscreen)
UR - https://www.scopus.com/pages/publications/84884888721
UR - https://www.scopus.com/pages/publications/84884888721#tab=citedBy
U2 - 10.1109/VR.2013.6549388
DO - 10.1109/VR.2013.6549388
M3 - Conference contribution
AN - SCOPUS:84884888721
SN - 9781467347952
T3 - Proceedings - IEEE Virtual Reality
SP - 113
EP - 114
BT - IEEE Virtual Reality Conference 2013, VR 2013 - Proceedings
T2 - 20th IEEE Virtual Reality Conference, VR 2013
Y2 - 16 March 2013 through 20 March 2013
ER -