Problem

Classic pinhole vanishing-point methods do not transfer directly to panoramas because image lines bend in equirectangular space and global spherical evidence is expensive to evaluate repeatedly.

Approach

• Detect local perspective line segments after cube projection to avoid equirectangular line distortion.
• Map line evidence onto a spherical parameter space and accumulate support in a lookup table.
• Sample and score Manhattan direction triplets efficiently with constant-time candidate evaluation.

My Contribution

I independently designed and implemented the complete panoramic vanishing point estimation module, from algorithm to C++ implementation and evaluation.

On the algorithm side, I built the core modules:

• Cube-face projection and line segment detection for distortion-free line extraction
• Spherical weighted lookup table construction enabling constant-time RANSAC candidate evaluation
• Manhattan triplet fitting under orthogonal constraints with brute-force sampling

Outcome

The module provides stable room orientation cues for downstream rectification, plane reasoning, and indoor reconstruction initialization.