TY - GEN
T1 - Accelerating Particle filter using multiscale methods
AU - Shmueli, Yaniv
AU - Shabat, Gil
AU - Bermanis, Amit
AU - Averbuch, Amir
PY - 2012
Y1 - 2012
N2 - We present a method that accelerates the Particle Filter computation. Particle Filter is a powerful method for tracking the state of a target based on non-linear observations. Unlike the conventional way of calculating weights over all particles in each run, we sample a small subset of the particles using matrix decomposition methods, followed by a novel function extension algorithm to recover the density function of all particles. This significantly reduces the computational load where the measurement computation is substantial, as often happens, for example, when tracking targets in videos. We demonstrate our method on both simulated data and real data (videos).
AB - We present a method that accelerates the Particle Filter computation. Particle Filter is a powerful method for tracking the state of a target based on non-linear observations. Unlike the conventional way of calculating weights over all particles in each run, we sample a small subset of the particles using matrix decomposition methods, followed by a novel function extension algorithm to recover the density function of all particles. This significantly reduces the computational load where the measurement computation is substantial, as often happens, for example, when tracking targets in videos. We demonstrate our method on both simulated data and real data (videos).
UR - http://www.scopus.com/inward/record.url?scp=84871955266&partnerID=8YFLogxK
U2 - 10.1109/EEEI.2012.6377009
DO - 10.1109/EEEI.2012.6377009
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AN - SCOPUS:84871955266
SN - 9781467346801
T3 - 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012
BT - 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012
T2 - 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, IEEEI 2012
Y2 - 14 November 2012 through 17 November 2012
ER -