Geographical Space Modeling for CGR via Image Classification

The patent applies preliminary action by performing image classification before correspondence search. The system pre-processes images to identify their geographical space correspondence, then uses this classification information to guide subsequent correspondence searches. This preliminary sorting step ensures that only relevant image pairs undergo computationally expensive correspondence analysis, significantly reducing overall processing time while maintaining model accuracy.

The patent introduces an image classification result as an intermediary between the raw image set and the correspondence search process. This intermediary layer filters and organizes images based on their geographical space characteristics, creating a structured subset of candidate image pairs. The intermediary classification results act as a guide that directs correspondence searches toward promising matches while avoiding futile comparisons between unrelated images.

The system performs preliminary image classification to identify geographical space correspondences before initiating correspondence searches. This pre-processing step creates a filtered set of candidate image pairs that are likely to share common features, thereby reducing the total number of computationally expensive correspondence operations required while maintaining model synthesis accuracy.

The patent applies partial action by performing correspondence searches only on a subset of image pairs identified as potential matches through classification, rather than exhaustively searching all possible pairs. This selective approach performs sufficient (but not excessive) correspondence analysis on relevant images, achieving accurate model synthesis with reduced computational resource consumption.

The patent segments the model synthesis process into distinct stages: image classification, correspondence search, and model synthesis. By dividing the overall task into separate functional modules, the system manages complexity through structured organization. Each module handles a specific aspect of the problem, making the overall system more tractable and maintainable despite the added procedural steps.

The image classification component serves multiple functions within the system: it pre-processes images for correspondence search, identifies geographical space relationships, and provides filtering criteria for subsequent processing stages. This multi-functionality justifies the added complexity by delivering multiple benefits from a single computational step.