About SummitSight

Advanced Geolocation Through Skyline Analysis

What is SummitSight?

SummitSight is an innovative geolocation tool that uses advanced computer vision and contour analysis to identify locations based on skyline images. By analysing the unique "fingerprint" of mountain ridges and horizons, we can match your uploaded images to known geographical locations in our database.

How It Works — Pipeline Walkthrough

Your image goes through a multi-stage processing pipeline:

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Upload Your mountain photo
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Segmentation SegFormer AI
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Curve Extraction Sky–terrain boundary
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FFT Search 1.35M fingerprints
🎯
Refinement KD-tree + scoring
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Results Top-5 locations
  • Segmentation: SegFormer extracts a sky mask from the photo using semantic segmentation
  • Curve Extraction: The sky–terrain boundary is traced as a 1-D elevation profile
  • FFT Coarse Search: Fast Fourier Transform cross-correlation scans 1.35 million pre-computed skyline fingerprints in ~14 chunks
  • KD-Tree Refinement: The top coarse matches are geographically clustered, then re-scored with NCC, Chamfer distance, RMSE and elevation weighting
  • Final Ranking: Composite confidence score combines all metrics to produce ranked candidates

How Confidence Is Calculated

Each candidate receives a confidence score from four factors. We normalize each metric, apply fixed weights, then combine them into a final score out of 100.

45% - NCC

Normalised cross-correlation captures skyline shape similarity between your query and database profile.

25% - Chamfer

Asymmetric Chamfer distance measures geometric closeness of the skyline boundary, robust to clutter.

15% - RMSE

Root mean square error penalizes profile mismatch in elevation angle across the aligned segment.

15% - Elevation Profile

Elevation-profile scoring checks whether terrain structure and ridge variation are physically plausible.

Confidence = 100 x (0.45 x NCC + 0.25 x Chamfer + 0.15 x RMSE + 0.15 x Elevation)

Technology Stack

Frontend

HTML5, CSS3 (dark mode), JavaScript, Leaflet.js maps, Canvas API charts

Backend

Node.js with Express proxy, Python Flask API for ML inference

AI Models

SegFormer semantic segmentation model for robust sky masking and skyline extraction

Search Engine

FFT cross-correlation on 1.35M skylines, KD-tree geographic refinement, NCC+Chamfer scoring

Database Coverage

SummitSight's database currently covers the Pyrenees mountain range with 1,347,655 viewpoints at 250 m resolution. Coverage is stored in seven uniform tiles shown below:

Coverage tiles: 7 (uniform)  |  Lat/Lon extent: 42°N – 44°N, 2°W – 3°E  |  Resolution: 250 m grid

Use Cases

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Hiking & Outdoor Recreation

Identify your location when hiking or exploring new terrain

📷

Photography

Rediscover where old landscape photos were taken

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Research

Geolocation analysis for scientific and academic purposes

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Exploration

Plan trips by identifying interesting mountain ranges

Tips for Best Results

  • Use clear images with visible skylines or mountain ridges
  • Avoid images with heavy fog, clouds, or obstructions
  • Higher resolution images typically provide better results
  • Images taken during clear weather conditions work best
  • Ensure the horizon is clearly visible in the photograph

Ready to Try It?

Upload your skyline image and discover your location!

Get Started