# Efficient Pedestrian Detection in Top-View Fisheye Images Using Compositions of Perspective View Patches

arXiv: https://arxiv.org/abs/2009.02711 · HTML: https://mlsanity.com/paper/2009.02711/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Sep 2020.

## Built on by (most cited first, 7 of 7)

- [Large-Scale Person Detection and Localization using Overhead Fisheye Cameras](https://mlsanity.com/paper/2307.08252/) (2023)
- [Applications of Deep Learning for Top-View Omnidirectional Imaging: A Survey](https://mlsanity.com/paper/2304.08193/) (2023)
- [Segmentation-Based Bounding Box Generation for Omnidirectional Pedestrian Detection](https://mlsanity.com/paper/2104.13764/) (2021)
- [Holistic Interpretation of Public Scenes Using Computer Vision and Temporal Graphs to Identify Social Distancing Violations](https://mlsanity.com/paper/2112.06428/) (2021)
- [Reinforced Pedestrian Attribute Recognition with Group Optimization Reward](https://mlsanity.com/paper/2205.14042/) (2022)
- [TSAA: A Two-Stage Anchor Assignment Method towards Anchor Drift in Crowded Object Detection](https://mlsanity.com/paper/2211.00826/) (2022)
- [GazeOnce360: Fisheye-Based 360deg Multi-Person Gaze Estimation with Global-Local Feature Fusion](https://mlsanity.com/paper/2603.17161/) (2026)

## Abstract (arXiv)

Pedestrian detection in images is a topic that has been studied extensively, but existing detectors designed for perspective images do not perform as successfully on images taken with top-view fisheye cameras, mainly due to the orientation variation of people in such images. In our proposed approach, several perspective views are generated from a fisheye image and then concatenated to form a composite image. As pedestrians in this composite image are more likely to be upright, existing detectors designed and trained for perspective images can be applied directly without additional training. We also describe a new method of mapping detection bounding boxes from the perspective views to the fisheye frame. The detection performance on several public datasets compare favorably with state-of-the-art results.