This paper proposes a method for identifying an object which contains an accelerometer out of many moving objects in the view of a stationary camera using motion data obtained by the camera and the accelerometer. The camera and the accelerometer are assumed to be connected with a network but not synchronized. In order to evaluate the similarity of the motion data despite the unknown time lag between the accelerometer and the camera, NCC (Normalized Cross-Correlation) of the signals is computed and its peak is tracked. Since the coordinate system of the accelerometer is unknown, NCC is computed for the norms of the acceleration vectors, which were compensated for the gravitational acceleration component, obtained by the camera and the accelerometer. The experimental results show that the proposed method successfully identified the person wearing the accelerometer out of three walking people. It is also shown that the hand holding the accelerometer was successfully identified out of three moving hands even though the directions of the accelerometer coordinate axes varied temporally due to the free motion of the hand.