Democratic Integration: Self-Organized Integration of Adaptive Cues

TLDR

Sensory integration, or sensor fusion, is a fundamental problem of perception in biological and artificial systems. The authors propose a self‑organized architecture that adaptively integrates multiple cues. In Democratic Integration, cues converge on a common result, suppress discordant cues, recalibrate them, and weight consistently aligned cues more heavily, as tested on face‑tracking. Experiments demonstrate robustness to sudden environmental changes affecting only a minority of cues at once, though all cues may be disrupted over time.

Abstract

Sensory integration or sensor fusion—the integration of information from different modalities, cues, or sensors—is among the most fundamental problems of perception in biological and artificial systems. We propose a new architecture for adaptively integrating different cues in a self-organized manner. In Democratic Integration different cues agree on a result, and each cue adapts toward the result agreed on. In particular, discordant cues are quickly suppressed and recalibrated, while cues having been consistent with the result in the recent past are given a higher weight in the future. The architecture is tested in a face tracking scenario. Experiments show its robustness with respect to sudden changes in the environment as long as the changes disrupt only a minority of cues at the same time, although all cues may be disrupted at one time or another.