Abstract:Tracking objects in 3D space and predicting their 6DoF pose is an essential task in computer vision. State-of-theart approaches often rely on object texture to tackle this problem. However, while they achieve impressive results, many objects do not contain sufficient texture, violating the main underlying assumption. In the following, we thus propose ICG, a novel probabilistic tracker that fuses region and depth information and only requires the object geometry. Our method deploys correspondence lines and poin… Show more
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