Conference proceeding
Self-organizing binary encoding for Approximate Nearest Neighbor search
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings, 1103
01 Jan 2016
Abstract
Conference Title: 2016 24th European Signal Processing Conference (EUSIPCO) Conference Start Date: 2016, Aug. 29 Conference End Date: 2016, Sept. 2 Conference Location: Budapest, Hungary Approximate Nearest Neighbor (ANN) search for indexing and retrieval has become very popular with the recent growth of the databases in both size and dimension. In this paper, we propose a novel method for fast approximate distance calculation among the compressed samples. Inspiring from Kohonen's self-organizing maps, we propose a structured hierarchical quantization scheme in order to compress database samples in a more efficient way. Moreover, we introduce an error correction stage for encoding, which further improves the performance of the proposed method. The results on publicly available benchmark datasets demonstrate that the proposed method outperforms many well-known methods with comparable computational cost and storage space.
Metrics
5 Record Views
Details
- Title
- Self-organizing binary encoding for Approximate Nearest Neighbor search
- Creators
- Ezgi Can OzanSerkan KiranyazMoncef GabboujXiaohua Hu
- Publication Details
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings, 1103
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Identifiers
- 991019170414504721