Optimized Pedestrian Detection for Multiple and Occluded People
We present a quadratic unconstrained binary optimization (QUBO) framework for reasoning about multiple object detections with spatial overlaps. The method maximizes an objective function composed of unary detection confidence scores and pairwise overlap constraints to determine which overlapping detections should be suppressed, and which should be kept. The framework is flexible enough to handle the problem of detecting objects as a shape covering of a foreground mask, and to handle the problem of filtering confidence weighted detections produced by a traditional sliding window object detector. In our experiments, we show that our method outperforms two existing state-ofthe-art pedestrian detectors.
Code (0)
등록된 구현이 없습니다.
Tasks
ObjectPedestrian DetectionSimilar Papers 제목 키워드 기반
Occluded Pedestrian Detection Through Guided Attention in CNNs
Pedestrian detection has progressed significantly in the last years. However, occluded people are notoriously hard to detect, as their appearance varies substantially depending on a wide range of partial occlusions. In t…
Pedestrian DetectionDiscriminative Feature Transformation for Occluded Pedestrian Detection
Despite promising performance achieved by deep con- volutional neural networks for non-occluded pedestrian de- tection, it remains a great challenge to detect partially oc- cluded pedestrians. Compared with non-occluded …
Pedestrian DetectionMask-Guided Attention Network for Occluded Pedestrian Detection
Pedestrian detection relying on deep convolution neural networks has made significant progress. Though promising results have been achieved on standard pedestrians, the performance on heavily occluded pedestrians remains…
Pedestrian DetectionMulti-Scale Feature Pyramid Network: A Heavily Occluded Pedestrian Detection Network Based on ResNet
The existing pedestrian detection algorithms cannot effectively extract features of heavily occluded targets which results in lower detection accuracy. To solve the heavy occlusion in crowds, we propose a multi-scale f…
Object DetectionPedestrian DetectionFeature Calibration Network for Occluded Pedestrian Detection
Pedestrian detection in the wild remains a challenging problem especially for scenes containing serious occlusion. In this paper, we propose a novel feature learning method in the deep learning framework, referred to as …
Pedestrian Detection