Title:
A CBR System for Efficient Face Recognition Under Partial Occlusion.
A CBR System for Efficient Face Recognition Under Partial Occlusion.
Authors:
López Sánchez, Daniel; González Arrieta, Angélica; Corchado Rodríguez, Juan M.
Book:
Case-Based Reasoning Research and Development: 25th International Conference, ICCBR 2017, Trondheim, Norway, June 26-28, 2017, Proceedings. Lecture Notes in Computer Science. Volume 10339, pp. 170-184.
Publication date:
21 June 2017
ISBN:
978-3-319-61029-0 (Print), 978-3-319-61030-6 (Online)
This work focuses on the design and validation of a CBR system for efficient face recognition under partial occlusion conditions. The proposed CBR system is based on a classical distance-based classification method, modified to increase its robustness to partial occlusion. This is achieved by using a novel dissimilarity function which discards features coming from occluded facial regions. In addition, we explore the integration of an efficient dimensionality reduction method into the proposed framework to reduce computational cost. We present experimental results showing that the proposed CBR system outperforms classical methods of similar computational requirements in the task of face recognition under partial occlusion.