A Comprehensive Approach for Camera/LIDAR Frame Alignment

Bouain, Mokhtar; Berdjag, Denis; Fakhfakh, Nizar; Atitallah, Rabıe Ben

doi:10.1007/978-3-030-11292-9_38

Informatics in Control, Automation and Robotics

2019

DOI: 10.1007/978-3-030-11292-9_38

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A Comprehensive Approach for Camera/LIDAR Frame Alignment

Mokhtar Bouain¹,

Denis Berdjag²,

Nizar Fakhfakh³

et al.

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“…Following this, for the vision module, a symmetry algorithm and a contour detection technique are applied to the ROIs to identify vehicles. The goal of the work presented in [45] is to detect pedestrians. Narrow-band radar sensor provides a list of tracks and the ACF object detector is adopted to generate a list of identified pedestrians in the images.…”

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OLIMP: A Heterogeneous Multimodal Dataset for Advanced Environment Perception

et al. 2020

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A reliable environment perception is a crucial task for autonomous driving, especially in dense traffic areas. Recent improvements and breakthroughs in scene understanding for intelligent transportation systems are mainly based on deep learning and the fusion of different modalities. In this context, we introduce OLIMP: A heterOgeneous Multimodal Dataset for Advanced EnvIronMent Perception. This is the first public, multimodal and synchronized dataset that includes UWB radar data, acoustic data, narrow-band radar data and images. OLIMP comprises 407 scenes and 47,354 synchronized frames, presenting four categories: pedestrian, cyclist, car and tram. The dataset includes various challenges related to dense urban traffic such as cluttered environment and different weather conditions. To demonstrate the usefulness of the introduced dataset, we propose a fusion framework that combines the four modalities for multi object detection. The obtained results are promising and spur for future research.

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OLIMP: A Heterogeneous Multimodal Dataset for Advanced Environment Perception

et al. 2020

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A Comprehensive Approach for Camera/LIDAR Frame Alignment

Cited by 1 publication

References 21 publications

OLIMP: A Heterogeneous Multimodal Dataset for Advanced Environment Perception

OLIMP: A Heterogeneous Multimodal Dataset for Advanced Environment Perception

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