Graph construction for visual data

Constructing graphs from visual data is a crucial step in applying graph-based methods to CV tasks. The choice of graph construction method can significantly impact the performance and interpretability of downstream tasks. This section explores various approaches to graph construction, each suited to different types of visual data and problem domains.

Pixel-level graphs

Pixel-level graphs represent images at their most granular level, with each pixel serving as a node in the graph. Edges are typically formed between neighboring pixels, creating a grid-like structure that mirrors the original image. This approach preserves fine-grained spatial information but can lead to large, computationally expensive graphs for high-resolution images.

For example, in a 100x100 pixel image, we would create a graph with 10,000 nodes. Each node might be connected to its four or eight nearest neighbors, depending on whether we consider diagonal connections...