Citizen Orb Photometry Pipeline (COPP): A Standardized Method for Computational Analysis of Anomalous Luminous Phenomena from Consumer Video Captures

Abstract

We present the Citizen Orb Photometry Pipeline (COPP), a standardized ten-step computational method for quantitative analysis of anomalous luminous phenomena (ALP) captured in consumer video recordings. The pipeline extracts frame-by-frame photometric measurements including centroid position, apparent size, peak and integrated intensity, RGB spectral channel decomposition, and derived metrics including blue excess, pulsation periodicity, and position discontinuities. A key methodological innovation is adaptive spectral measurement: when sensor saturation renders core color data unreliable, the pipeline automatically shifts spectral analysis to the unsaturated halo region, enabling consistent cross-case comparison regardless of source brightness or observer distance. We demonstrate COPP through comparative analysis of three ALP captures spanning fourteen years, three countries, and distinct observational conditions: a distant, mobile, spectrally cool orb over the Taiwan coast (2021); a close-range, stationary, spectrally warm orb in the United Kingdom (2011); and a close-range, stationary orb with correlated size-color pulsation in Poland (2025). Despite differences in apparent brightness, angular size, and sensor saturation state, all three cases exhibit spectral overlap consistent with a common emission mechanism. Signal structure analysis of the Taiwan case reveals strong size-intensity correlation (r = 0.808) and quasi-periodic pulsation, indicating non-random temporal structure. COPP addresses a documented gap between professionally calibrated instruments and citizen capture platforms by providing a standardized computational bridge that runs in standard Python environments and processes any consumer video format. The COPP v1.0 pipeline demo is available as a working prototype at https://copp-w.vercel.app/.  The purpose of this paper is to place the method and its outputs in the public domain in a form others can inspect, critique and extend, and we invite the community to test the pipeline against their own captures and to help make it more reliable and more consistent.