•1 min read•from Machine Learning
[P] Best approach for online crowd density prediction from noisy video counts? (no training data)
I have per-frame head counts from P2PNet running on crowd video clips. Counts are stable but noisy (±10%). I need to predict density 5-10 frames ahead per zone, and estimate time-to-critical-threshold.
Currently using EMA-smoothed Gaussian-weighted linear extrapolation. MAE ~20 on 55 frames. Direction accuracy 49% (basically coin flip on reversals).
No historical training data available. Must run online/real-time on CPU.
What would you try? Kalman filter? Double exponential smoothing? Something else?
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