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Comet and Target Ghost: Techniques for Selecting Moving Targets
Enabling User Interactions with Video ContentsKhalad Hasan, Yang Wang, Wing Kwong and Pourang Irani
Motion Control2
3
End CallVoice Control 4
Face Recognition5Gaps Interaction with video contents Suitable querying and interface component Selection techniqueMotivation6Gaps Interaction with video contents Suitable querying and interface component Selection techniqueMotivation7Computer Vision Comparison among state-of-art algorithms Apply best algorithm to extract objects
HCI Interaction with video contents Techniques for selectionContributionObject Detection & Tracking89
Tracking-Learning-Detection (TLD): Kalal et al.Datasets: http://vision.ucsd.edu/~bbabenko/project_miltrack.shtml10
Struck: Hare et al.11StruckTLDStruckTLDTime(sec)Time(sec)Frame/SecFrame/SecCoke251471.166.21Girl401931.325.69Tiger1394530.906.68Tiger2334621.095.89Average345.0063.751.126.12Speed Comparison12TLDStruckCoke0.940.69Girl0.930.80Tiger10.860.77Tiger20.790.63Average0.880.72PrecisionInteractions
1314Input Device
15Kinect Input
Static Target Selection
TargetMoving Target Selection
18Selection Techniques Left-hand with Basic Left-hand with Ghost Left-hand with Crossing
Depth with Basic Depth with Ghost Depth with Crossing19Selection Techniques Left-hand with Basic
Action
Target Ghost (Khalad et al. CHI 2011)21Selection Techniques Left-hand with Ghost
22Selection Techniques Left-hand with Crossing
23Selection TechniquesSelection Left-hand Depth
24ResultsTechniqueBasic Ghost CrossingTask Completion Time (ms)6,000
4,000
2,000
0 Left-handDepth25ResultsTechniqueBasic Ghost CrossingAverage Number of Attempts2.0
1.5
1.0
0.5
0 Left-handDepth26
27Take-Home TLD is faster & accurate Both hands for Kinect based interactions Selection is best achieved with static proxies28Future workComputer Vision Multiple tracked objects Online detection & tracking
HCI Selection Techniques New form of interactions with KinectThank you