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Tradition gait analysis systems capture the image of a walking subject from either front view or side view. Since the walking direction allowed by the systems is highly restricted, they are inconvenient for long-term evaluation in casual environments (such as home). This study proposes a human gait analysis system with much less restriction on walking direction. In the system, we use the images obtained from multi-viewing angles and performs human gait analysis based on a set of chosen features, including the center of gravity (COG) and pace length, obtained from human silhouette images. The system successfully extracts gait features from various walking directions and integrates the features obtained from two cameras having orthogonal views. The integration principle is discussed in details. The integrated feature is then compared with the ideal gait feature obtained from the camera whose viewing direction is perpendicular to the walking path, resulting in very high correlation. This study shows that a vision-based gait analyzer with two orthogonally arranged cameras has the potential to remove the walking direction restriction.