Ten-fold Improvement in Visual Odometry Using Landmark Matching

Our goal is to create a visual odometry system for robots and wearable systems such that localization accuracies of centimeters can be obtained for hundreds of meters of distance traveled. Existing systems have achieved approximately a 1% to 5% localization error rate whereas our proposed system achieves close to 0.1% error rate, a ten-fold reduction. Traditional visual odometry systems drift over time as the frame-to-frame errors accumulate. In this paper, we propose to improve visual odometry using visual landmarks in the scene. First, a dynamic local landmark tracking technique is proposed to track a set of local landmarks across image frames and select an optimal set of tracked local landmarks for pose computation. As a result, the error associated with each pose computation is minimized to reduce the drift significantly. Second, a global landmark based drift correction technique is proposed to recognize previously visited locations and use them to correct drift accumulated durin...

• Type: Conference
• Year: 2007
• Where: ICCV
• Authors: Zhiwei Zhu, Taragay Oskiper, Supun Samarasekera, Rakesh Kumar, Harpreet S. Sawhney
• Keywords: Computer Vision, ICCV 2007, Local Landmarks, Visual Landmarks, Visual Odometry