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