# A Robust Visual System for Small Target Motion Detection Against Cluttered Moving Backgrounds

## TL;DR

This paper introduces a novel visual system model inspired by insect neurons that improves small target motion detection in cluttered backgrounds by reducing false positives through a contrast pathway.

## Contribution

The proposed STMD+ model integrates contrast and motion pathways for better discrimination of real targets from background features, advancing insect-inspired robotic vision.

## Key findings

- Significant reduction in false positives compared to existing models
- Enhanced detection accuracy of small targets in cluttered scenes
- Robust performance against fake background features

## Abstract

Monitoring small objects against cluttered moving backgrounds is a huge challenge to future robotic vision systems. As a source of inspiration, insects are quite apt at searching for mates and tracking prey -- which always appear as small dim speckles in the visual field. The exquisite sensitivity of insects for small target motion, as revealed recently, is coming from a class of specific neurons called small target motion detectors (STMDs). Although a few STMD-based models have been proposed, these existing models only use motion information for small target detection and cannot discriminate small targets from small-target-like background features (named as fake features). To address this problem, this paper proposes a novel visual system model (STMD+) for small target motion detection, which is composed of four subsystems -- ommatidia, motion pathway, contrast pathway and mushroom body. Compared to existing STMD-based models, the additional contrast pathway extracts directional contrast from luminance signals to eliminate false positive background motion. The directional contrast and the extracted motion information by the motion pathway are integrated in the mushroom body for small target discrimination. Extensive experiments showed the significant and consistent improvements of the proposed visual system model over existing STMD-based models against fake features.