Multi-view Aggregation for Color Naming with Shadow Detection and Removal

Dahy Elkhouly, Mohamed; James, Stuart; Del Bue, Alessio

Abstract

This paper presents a set of methods for classifying the color attribute of objects when multiple images of the same objects are available. This problem is more complex than the single image estimation since varying environmental effects, such as, shadows or specularities from light sources, can result in poor accuracy. These depend primarily on the camera positions and the material type of the objects. Single image techniques focus on improving the discrimination of between colors, whereas in multi-view systems additional information is available but should be utilized wisely. To this end, we propose three methods to aggregate image pixel information in multi-view that boost the performance of color name classification. Moreover, we study the effect of shadows by employing automatic shadow detection and correction techniques on the color naming problem. We tested our proposals on a new multi-view color names dataset (M3DCN) which contain indoor and outdoor objects. The experimental evaluation shows that one out of the three presented aggregation methods is very efficient and it achieves the highest accuracy in term of classification results. Also, we experimentally show that addressing visual outliers like shadow in multi-view images improves the performance of the color attribute decision process.

Citation

Dahy Elkhouly, M., James, S., & Del Bue, A. (2018, December). Multi-view Aggregation for Color Naming with Shadow Detection and Removal. Presented at 2018 IEEE International Conference on Image Processing, Applications and Systems (IPAS), Sophia Antipolis, France

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2018 IEEE International Conference on Image Processing, Applications and Systems (IPAS)
• Start Date: Dec 12, 2018
• End Date: Dec 14, 2018
• Online Publication Date: May 9, 2019
• Publication Date: 2018
• Deposit Date: Dec 13, 2023
• Publisher: Institute of Electrical and Electronics Engineers
• Book Title: 2018 IEEE International Conference on Image Processing, Applications and Systems (IPAS)
• ISBN: 9781728102481
• DOI: https://doi.org/10.1109/IPAS.2018.8708885
• Public URL: https://durham-repository.worktribe.com/output/2024590