Image-based view synthesis by combining trilinear tensors and learning techniques
VRST '97 Proceedings of the ACM symposium on Virtual reality software and technology
Novel View Synthesis by Cascading Trilinear Tensors
IEEE Transactions on Visualization and Computer Graphics
Projective Structure from Uncalibrated Images: Structure From Motion and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algebraic Functions For Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Construction of Virtual Environment from Video Data with Forward Motion
AMCP '98 Proceedings of the First International Conference on Advanced Multimedia Content Processing
View synthesis using stereo vision
View synthesis using stereo vision
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It is commonly assumed that the goal of stereovision is computing explicit 3D scene reconstructions. We show that very accurate camera calibration is needed to support this, a''nd that such accurate calibration is difficult to achieve and maintain. We argue that for tasks like recognition, figure/ground separation is more important than 3D depth reconstruction, and demonstrate a stereo algorithm that supports figure/ground separation without 3D reconstruction.