This work addresses pedestrian detection in surveillance video under the conditions that break standard detectors: occlusion, noise, and partial views. The method regularizes conditional random fields with fractal-geometric structure, holding detection accuracy where conventional CRF pipelines degrade.
Read the full paper at Tech Science Press (DOI 10.32604/jai.2026.082982) →
It extends the earlier work on people detection from partial gait cycles.