Activity Recognition through Goal-Based Segmentation

DESCRIPTION

This paper presents a goal-based segmentation approach for activity recognition utilizing a probabilistic segmentation model tailored for wireless environments. Leveraging signal-strength readings and motion patterns, it illustrates how high-level goals can be identified from low-level signal segments. Each defined segment represents a specific motion pattern, thereby reducing the human effort required in the calibration of activity recognition systems. The findings contribute to enhanced understanding and application of sensory data for accurate activity inference.

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Feb 14, 2026

1 activity recognition 2 goalbased segmentation 3 wireless environments 4 probabilistic model 5 motion patterns 6 signalstrength readings 7 sensory data 8 calibration reduction text

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Activity Recognition through Goal-Based Segmentation

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Activity Recognition through Goal-Based Segmentation Jie Yin, Dou Shen, Qiang Yang and Ze-Nian Li, AAAI 2005 • Application Domain: Wireless Environment • Probabilistic Segmentation Model • Trace Database on Signal-Strength Readings Motion Pattern: • Illustration on Sensory data • Goal-Based Segmentation algorithm • High-level goals can be recognized from low-level signal segments • Each segment define a motion pattern Reduce human effort in calibration for activity recognition!