Segmentation-Based Bounding Box Generation for Omnidirectional Pedestrian Detection

TL;DR

This paper introduces a segmentation-based method for generating tight bounding boxes in omnidirectional pedestrian detection, leveraging existing datasets and distortion augmentation to improve accuracy without extensive annotation or image transformation.

Contribution

The authors propose a novel segmentation-based bounding box generation technique that eliminates the need for omnidirectional image training and reduces annotation costs.

Findings

Effective bounding box fitting in omnidirectional images

Significant performance improvements over existing methods

Enhanced detection accuracy with pseudo-fisheye distortion augmentation

Abstract

We propose a segmentation-based bounding box generation method for omnidirectional pedestrian detection that enables detectors to tightly fit bounding boxes to pedestrians without omnidirectional images for training. Due to the wide angle of view, omnidirectional cameras are more cost-effective than standard cameras and hence suitable for large-scale monitoring. The problem of using omnidirectional cameras for pedestrian detection is that the performance of standard pedestrian detectors is likely to be substantially degraded because pedestrians' appearance in omnidirectional images may be rotated to any angle. Existing methods mitigate this issue by transforming images during inference. However, the transformation substantially degrades the detection accuracy and speed. A recently proposed method obviates the transformation by training detectors with omnidirectional images, which instead incurs huge annotation costs. To obviate both the transformation and annotation works, we leverage an existing large-scale object detection dataset. We train a detector with rotated images and tightly fitted bounding box annotations generated from the segmentation annotations in the dataset, resulting in detecting pedestrians in omnidirectional images with tightly fitted bounding boxes. We also develop pseudo-fisheye distortion augmentation, which further enhances the performance. Extensive analysis shows that our detector successfully fits bounding boxes to pedestrians and demonstrates substantial performance improvement.