An Improved LPTC Neural Model for Background Motion Direction Estimation

TL;DR

This paper introduces a max operation mechanism inspired by a newly discovered neuron to enhance background motion direction estimation by filtering irrelevant signals, improving upon existing models like EMD and TQD.

Contribution

The paper proposes a novel max operation mechanism based on Tm9 neuron properties to improve TQD model performance in cluttered backgrounds.

Findings

Enhanced detection accuracy in cluttered environments

Effective filtering of irrelevant motion signals

Improved background motion perception

Abstract

A class of specialized neurons, called lobula plate tangential cells (LPTCs) has been shown to respond strongly to wide-field motion. The classic model, elementary motion detector (EMD) and its improved model, two-quadrant detector (TQD) have been proposed to simulate LPTCs. Although EMD and TQD can percept background motion, their outputs are so cluttered that it is difficult to discriminate actual motion direction of the background. In this paper, we propose a max operation mechanism to model a newly-found transmedullary neuron Tm9 whose physiological properties do not map onto EMD and TQD. This proposed max operation mechanism is able to improve the detection performance of TQD in cluttered background by filtering out irrelevant motion signals. We will demonstrate the functionality of this proposed mechanism in wide-field motion perception.