Philippe Lavoie

University of Ottawa, Quattriuum (Canada)

Papers

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About

Philippe Lavoie is a researcher whose work bridges the critical fields of 3D computer vision, object reconstruction, and indoor localization. His most significant contributions lie in developing methods for recovering three-dimensional object models from two-dimensional images, a foundational challenge in CAD/CAM, robotics, and remote sensing. In his highly cited 2004 work, "3D object model recovery from 2D images using structured light" (54 citations), Lavoie advanced techniques for precise 3D shape acquisition, enabling more accurate digital modeling from physical objects. He further refined these concepts in his earlier 1996 paper on 3D reconstruction using uncalibrated stereo pairs of encoded images, demonstrating early innovation in simplifying the reconstruction pipeline. Expanding beyond static vision, Lavoie also made notable strides in indoor tracking technology. His 2014 paper on "RSSI-based indoor tracking using the extended Kalman filter and circularly polarized antennas" (32 citations) addresses the practical challenge of localizing mobile emitters in complex indoor environments. By integrating signal strength indicators with advanced filtering and specialized antenna design, this work has implications for robotics, smart environments, and navigation systems where GPS is unavailable. Through these diverse contributions, Lavoie has demonstrated a sustained impact on both the theoretical and applied aspects of 3D sensing and spatial intelligence.