Intrinsic or data-driven respiratory and cardiac motion detection often track the center-of-mass (COM) change in PET data to derive a motion gating signal. The effectiveness of this method depends on the contrast of the moving target to the relatively stationary background. The stationary background leads to a reduced COM displacement in PET data. Further, the COM calculated using axially truncated PET data is biased. To improve intrinsic motion detection for motion compensated image reconstruction, we use the time-of-flight (TOF) PET data of the original object f(x) to calculate the non-TOF PET data of a volume-of-interest (VOI) weighted object f(x)w(x) . The VOI-weighting w(x) can be chosen to reduce contribution from the stationary background. The reduced background in f(x)w(x) leads to an observed increase in the COM displacement. We also derive rebinning equations to obtain the exact axial COM using axially truncated PET data. To assess the quality of the motion gating signal, we analyze the variance property of the COM using different methods, including with(out) VOI weighting and with(out) compensation for axial data truncation. Analytical simulations, phantom and patient data demonstrate the effectiveness of the proposed approach in identifying the motion phase and in deriving a gating signal to be used for motion-compensated image reconstruction.