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. Author manuscript; available in PMC: 2012 Sep 6.
Published in final edited form as: IEEE Trans Med Imaging. 2011 Aug 22;31(1):117–130. doi: 10.1109/TMI.2011.2165554

Fig. 5.

Fig. 5

Comparison of the tracking performance obtained using three particle filtering algorithms. These data correspond to frames 42, 50, 52, 55, 61, and 77 of Movie 1 with SNR = 7.5, which is the same sequence shown in Fig. 1(a)–(f) and Fig. 3(a), (c), and (e). (a) GPF with 100 particles. (b) GPF with 200 particles. (c) OCPF with 50 particles. (d) OCPF with 100 particles. (e) SCPF with 50 particles. The upper row of panels in (a)–(e) show the distribution of the particles, which are represented as rectangular bounding boxes. The bounding boxes measure 10 × 130 pixels throughout. The bottom row of panels in (a)–(e) show tracking results overlaid on the image of the moving neurofilament, with insets showing the object tracking area at higher magnification. The position of the bounding box relative to the image of the filament is an indication of the tracking performance. GPF and OCPF generate many tracking errors in position and orientation. SCPF generates more accurate tracking performance with fewer particle numbers, resulting in a more efficient tracking method.