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# A Novel Sequence Representation for Unsupervised Analysis of Human Activities - PowerPoint PPT Presentation

A Novel Sequence Representation for Unsupervised Analysis of Human Activities. Presented by: Wei Pan For CS88/188. The Unsupervised Activity Classification System. Length . A 40-page paper. Straight-forward way of thinking of a problem. No graph model, no inference, no fancy math.

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### A Novel Sequence Representation for Unsupervised Analysis of Human Activities

Presented by: Wei Pan

For CS88/188

Length Human Activities

• A 40-page paper.

• Straight-forward way of thinking of a problem.

• No graph model, no inference, no fancy math.

Definition Human Activities

• Key Object

• Fridge, washer, stove, sink…

• Event

• Interaction among a subset of key objects in a certain time. (turn stove on; eat egg; fry egg)

• Activity

• A sequence of events with temporal order.

• Activity Structure

• The event sequence of an activity.

Definition Human Activities

• n-gram Histogram

• An Activity could be represented by a subset of its sequence.

Definition Human Activities

• Is n-gram real work?

• Under certain assumption it works!

• Simulation with VMMC.

• VMMC: A sampling method (in this paper) to generate sequences of different classes with noise.

Unsupervised Classification Human Activities

• Distance Measurement.

• Clustering Algorithm.

• Cluster Modeling.

Problem #1 Human Activities

• Distance between two activities?

• Y, Z are events in A and B respectively. K is normalization factor.

Problem #2 Human Activities

• Clustering Algorithm

• A max clique is a class.

• Dominant set algorithm. ([Pavan2003])

Problem #3 Human Activities

• Each activity is one of the two types:

• Regular

• Anomalous

• Each class has typical nodes.

• Calculated through [Kleinburg99]

Problem #4 Human Activities

• How to understand anomalous activities in a class?

UPS Load Dock Human Data Human Activities

• 1 month, Human Activities9am-5pm, 5 days a week

• 61 events, 10 key objects

• 195 activities, 150 labelled

• 7 major classes detected. (Table 1)

Residential House Sensor Data Human Activities

• 5 months

• 16 Strain gages

• 16 event

• every day is an activity

Residential House Sensor Data Human Activities

• People seems to have different plans for different day.

• 5 classes mined out. (Table 2)

Kitchen Vision Data Human Activities

Anomalous Analysis Works detected?

• Discover some anomalous activities

• Truck left with door open

• Someone cleaning up the floor

### Activity-Class Characterization detected?

Presented by: Wei Pan

For CS88/188

• Find a sequence of events detected?s, so that s will have a certain prediction power in all activities of class c. Thus s will be a motif of class c.

• Prediction power is analytically described as a bit-gain.