analyzing gaming-simulations using video based techniques
DESCRIPTION
Bharath Palavalli, Harsha Krishna and Dinesh Jayagopi. IIIT BangaloreTRANSCRIPT
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Dinesh Babu Jayagopi, Assistant Professor, IIIT Bangalore Co authors: Bharath and Harsha, Fields of View, India TEEM 2014, Gamification Ecosystems, 2 Oct 2014
Analyzing gaming simulations using video based techniques
+Energy game: a sample session
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Goal of the group: Energy policy for the country Observe 3 small groups
(representing departments – coal, atomic, renewable) Conflict/ Cooperation among groups Conflict/ Cooperation across groups
Goal serious Game designer: • Use game elements to maximize learning • Create awareness • Abstract reality
+Role of game observation
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+Quantitative data
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+Qualitative data: game observation
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n Group 1 (Dept of Atomic Energy) had heavy discussions
n Individual 2 in Group 3 was negotiating with Group 2 and was quite influential
n Individual 3 in Group 2 was dominating and disturbing
Behavior Analysis of Group dynamics
Group 1
Group 2 Group 3
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Behavior (Multimodal / audio-visual) analysis of group interactions
+Human Communication: Several channels of info.
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+Behavior Coding: extracting cues
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Source: Adam Kendon Conducting Interaction
+Technological trends: Human-centered Sensing
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Microcone – Array microphone
Kinect – Image + Depth Camera
Sociometer – Wearable badge
Google glasses
+Technological trends: Human-centered Signal Processing
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+Technological trends: Human-centered Signal Processing
© CHIL
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Label
Observations
Hidden Variable
Observations
Technological trends: Machine Learning/Probabilistic Formulations
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+Behavior Tracking and Perception [Human Human Interaction]
Cue Summarization
Behavior Perception
Multimodal Signal Processing
Speaking, Looking Gesturing style
Who speaks, Looks at Whom, who nods
Feedback/Analysis
Machine Learning
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Sensing
P(Perception/Behavior)
Behavior Tracking
VIDEO
+Example: Gaze tracking
VFOA: Visual Focus of Attention
Observation: Texture (HOG) & color features
State space:
Location, scale,
eccentricity - continuous
Pose – discrete
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+ 15 Example: Analysis HHI
speaking activity
inferred focus
person ID
head pose
tracking
side-view cameras
VIDEO
+Conclusion
n Serious game [Face-to-face] design
n Need for automatic observation (summarization and querying)
n Automatic behavior analysis
n Speech – who speaks when to whom, interruption, negotiation, word usage, dialog acts (question, answer)
n Video – who looks at whom, who gestures what
n Challenges: Canceling speech interference from other groups, occlusion.
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