Detecting Independent Motion: The Statistics of Temporal Continuity

Authors:
Robert Pless;Tomásˇ Brodský;Yiannis Aloimonos
Affiliations:
Univ. of Maryland, College Park;Philips Research, Briarcliff Manor, NY;Univ. of Maryland, College Park
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
2000

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Abstract

We consider a problem central in aerial visual surveillance applications驴detection and tracking of small, independently moving objects in long and noisy video sequences. We directly use spatiotemporal image intensity gradient measurements to compute an exact model of background motion. This allows the creation of accurate mosaics over many frames, and the definition of a constraint violation function which acts as an indicator of independent motion. A novel temporal integration method maintains confidence measures over long subsequences without computing the optic flow, requiring object models, or using a Kalman filter. The mosaic acts as a stable feature frame, allowing precise localization of the independently moving objects. We present a statistical analysis of the effects of image noise on the constraint violation measure and find a good match between the predicted probability distribution function and the measured sample frequencies in a test sequence.