Evaluation of multi-channel LiDAR Image modalities for LiDAR-only object detection

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School of Electrical Engineering | Master's thesis

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en

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53

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Abstract

This thesis investigates LiDAR-only object detection using multiple image modalities derived from a single multi-channel LiDAR sensor. Range, reflectivity, signal strength, and near-infrared (NearIR) outputs from an Ouster OS1-64 LiDAR are represented as two-dimensional images and evaluated within a unified YOLOv8-based detection framework under identical training and evaluation conditions. Single-modality experiments show that NearIR and reflectivity provide the strongest detection performance, while range images alone perform poorly due to their limited visual structure. Multi-modality experiments using early and late fusion reveal that certain modality combinations improve detection accuracy, whereas others yield diminishing returns due to less complementary interactions between modalities. The results further highlight practical limitations of LiDAR-only detection in cluttered environments, at long ranges, and on low-reflectivity surfaces. In summary, this study provides a comparative assessment of LiDAR image modalities and establishes an empirical foundation for future research on intra-LiDAR fusion strategies within LiDAR-only perception systems.

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Supervisor

Kucner, Tomasz

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Tikkanen, Tommi
Kutila, Matti

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