Depth and Thermal Image Fusion for Human Detection with Occlusion Handling Under Poor Illumination from Mobile Robot
| Autor: | Usman Ullah Sheikh, Saipol Hadi Hasim, Shamsuddin H. M. Amin, Rosbi Mamat |
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| Rok vydání: | 2016 |
| Předmět: |
050210 logistics & transportation
Image fusion business.industry Computer science 05 social sciences ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Mobile robot 02 engineering and technology Region of interest Minimum bounding box 0502 economics and business Occlusion Thermal 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Robot vision Artificial intelligence business Classifier (UML) ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | Emerging Trends and Advanced Technologies for Computational Intelligence ISBN: 9783319333519 |
| DOI: | 10.1007/978-3-319-33353-3_19 |
| Popis: | In this paper we present a vision-based approach to detect multiple persons with occlusion handling from a mobile robot in real-world scenarios under two lighting conditions, good illumination (lighted) and poor illumination (dark). We use depth and thermal information that are fused for occlusion handling. First, a classifier is trained using thermal images of the human upper-body. This classifier is used to obtain the bounding box coordinates of human. The depth image is later fused with the region of interest obtained from the thermal image. Using the initial bounding box, occlusion handling is performed to determine the final position of human in the image. The proposed method significantly improves human detection even in crowded scene and poor illumination. |
| Databáze: | OpenAIRE |
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