Beyond Landmark Extraction: A Framework for Robust Geometric Feature Construction in Structured Image Classification
Much of the literature on structured image recognition has disproportionately focused on the comparison of classification algorithms. Rather than investigating which classifier performs best, this paper instead asks: what should a classifier know before it ever makes a prediction? In structured vision problems such as gesture recognition, facial expression categorization, and medical image analysis, discriminative information lies less in individual pixels and more in spatial relationships between semantic parts. Raw pixel spaces are high-dimensional, sensitive to nuisance variation, and often obfuscate the geometric structures that make visual tasks interpretable. Landmark extraction pro...
| Authors | Saravana Mauree, Sakshi Arya |
|---|---|
| Primary category | cs.CV |
| Published | 1 September 2026 |
| Last updated at source | 2 September 2026 |
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