Special issue on image feature detection and description

Citation

Pang Y, Cao X, Zhang L & Hussain A (2013) Special issue on image feature detection and description. Neurocomputing, 120, pp. 1-3. http://www.scopus.com/inward/record.url?partnerID=yv4JPVwI&eid=2-s2.0-84874595196&md5=933a2facfdf28c95d596ed1edf560969; https://doi.org/10.1016/j.neucom.2013.02.036

Abstract
First paragraph: The state-of-the-art machine leaning and pattern recognition techniques have greatly push forwards the developments of computer vision. Image features are input of such learning and recognition algorithms. Therefore, the quality of image features bounds the performances of the learning and recognition algorithms. Robust, discriminative, and efficient image features (e.g. SIFT) can significantly improve the performances of image/video retrieval, recognition, tracking, biometrics, matching, registration, reconstruction, etc. This special issue aims at bringing together the state-of-the-art research results on image feature detection and description.

Notes
Output Type: Editorial

Journal
Neurocomputing: Volume 120