Bike riding is very popular and a good bike riding simulator would require a photorealistic view synthesizer to engage riders into the exercise atmosphere of the virtual environment. Therefore, this work focuses on using captured range-scanned point samples and scene photos to build a real-time realistic walk-through view synthesis system for a field riding bike simulator. Careful observation reveals that different parts of a field environment require different representations to achieve photorealistic appearance with proper memory consumption and proper rendering cost. The view synthesizer is built based on decomposing a field riding environment into several different representations based on their context and distances to the field. These representations include close-distanced view-dependent-texturing geometry-based objects, medium-distanced concentric-cylinder-image-based objects, long-distanced image-based objects, view-dependent-billboard-based vegetation and view-dependent geometry-based ground. Using different representations allows the system to choose different rendering techniques to generate the photorealitic appearance of a complex scene with affordable memory usage in interactive frame rates. Therefore, after collecting the input range-scanned point clouds and unorganized photos, the system first registers the range-scanned point clouds and unorganized photos to form a consistent range data and imagery. The photos are segmented into context patches based on their color and their depth projection from the point cloud. Finally, the patches and corresponding depth projections are used to reconstruct the representations for all different components. Later, these decomposed representations can be used to real-time synthesize photorealistic views required for interactively riding through the field.

Bike riding is very popular and a good bike riding simulator would require a photorealistic view synthesizer to engage riders into the exercise atmosphere of the virtual environment. Therefore, this work focuses on using captured range-scanned point samples and scene photos to build a real-time realistic walk-through view synthesis system for a field riding bike simulator. Careful observation reveals that different parts of a field environment require different representations to achieve photorealistic appearance with proper memory consumption and proper rendering cost. The view synthesizer is built based on decomposing a field riding environment into several different representations based on their context and distances to the field. These representations include close-distanced view-dependent-texturing geometry-based objects, medium-distanced concentric-cylinder-image-based objects, long-distanced image-based objects, view-dependent-billboard-based vegetation and view-dependent geometry-based ground. Using different representations allows the system to choose different rendering techniques to generate the photorealitic appearance of a complex scene with affordable memory usage in interactive frame rates. Therefore, after collecting the input range-scanned point clouds and unorganized photos, the system first registers the range-scanned point clouds and unorganized photos to form a consistent range data and imagery. The photos are segmented into context patches based on their color and their depth projection from the point cloud. Finally, the patches and corresponding depth projections are used to reconstruct the representations for all different components. Later, these decomposed representations can be used to real-time synthesize photorealistic views required for interactively riding through the field.

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