A highly accurate estimation method of 3-D pedestrian trajectories from walking activity sensing data is proposed. This method uses data from an accelerometer, a gyrometer, and an air pressure sensor, and does not require detailed information on the building structure. In activity sensing using wearable sensors, higher accuracy can be expected from detection of zones in which there is continuously little change in the states of the sensor signals than from detection of zones in which there are large changes in the sensor signals within a short time. We focus on such stability of sensing signal and, as an application example, we used the concept to estimate walking direction on the basis of stable walking zone detection using a gyrometer and estimation of movement between the floors of a building by detection of stable floor zones with an air pressure sensor. We then integrated these estimations to obtain a 3-D pedestrian trajectory. The results of evaluation experiments using an indoor pedestrian sensing corpus (HASC-IPSC) showed that this method achieved higher accuracy for both walking direction and movement between floors than was achieved by a method based on large changes in the sensor signals. We also confirmed that the cumulative error rate for estimation of the 3-D pedestrian trajectory was 1 m per 10 seconds of movement.