Kapitel 7 Touch vs. In-Air

• Landmark knowledge

• Procedural / route knowledge

• Surface knowledge

isometric: thinkpad red dot

isotonic: mouse no different resistanz static

radar sensing

• -> Uses modulated electromagnetic waves sent toward moving or static targets

• targets scatter transmitted radiation -> some portion of the energy is redirected back

• reflection gets measured by antenna

-> infos about target properties like time delay, phase, frequency shift are captured

Example: Google Soli

• Does not actually capture the skeletal structure

• Does not actually track the hand

• Requires machine learning techniques

live mic phenomenon -> every movement gets checked -> many FPs

• you are always “on-air”

possible that other person can use gesture to controll your phone

radar sensor -> in google phone can track hand gestures

• use case: phone is on table -> you can interact with it without touching

• ! but most of the time our phone is in pocket -> can not be used there

• Develop a matching gesture language

• Differentiate between interactions and not between systems

• Use specific gestures within your system

• Test basic interactions with users

• Consider false-positives and false-negatives

• Build your interaction concept from scratch

• you are always “on-air” -> every movement needs to be evaluated (battery, many FP)

• touch: interaction with surface, precise, direct input, only 2D

• in-air: no touching surface, doesnt require free hands, often less precise, 2D or 3D, always “on-air”