A Novel Wide-Area Multiobject Detection System with High-Probability Region Searching

TL;DR

This paper introduces a hybrid wide-area detection system combining panoramic imaging and high-speed search to efficiently locate multiple objects in large areas, achieving high frame rates and improved accuracy.

Contribution

The paper presents a novel method using panoramic probability maps and dynamic search modules for fast, accurate multi-object detection in wide-area surveillance.

Findings

Achieves 120 fps multi-object detection.

Effectively estimates high-probability regions for objects.

Demonstrates robustness in extensive experiments.

Abstract

In recent years, wide-area visual surveillance systems have been widely applied in various industrial and transportation scenarios. These systems, however, face significant challenges when implementing multi-object detection due to conflicts arising from the need for high-resolution imaging, efficient object searching, and accurate localization. To address these challenges, this paper presents a hybrid system that incorporates a wide-angle camera, a high-speed search camera, and a galvano-mirror. In this system, the wide-angle camera offers panoramic images as prior information, which helps the search camera capture detailed images of the targeted objects. This integrated approach enhances the overall efficiency and effectiveness of wide-area visual detection systems. Specifically, in this study, we introduce a wide-angle camera-based method to generate a panoramic probability map (PPM) for estimating high-probability regions of target object presence. Then, we propose a probability searching module that uses the PPM-generated prior information to dynamically adjust the sampling range and refine target coordinates based on uncertainty variance computed by the object detector. Finally, the integration of PPM and the probability searching module yields an efficient hybrid vision system capable of achieving 120 fps multi-object search and detection. Extensive experiments are conducted to verify the system's effectiveness and robustness.