IMAGE THUMBNAILING VIA MULTI-VIEW FACE DETECTION AND SALIENCY ANALYSIS
Chih-Chao Ma, Yi-Hsuan Yang, and Winston Hsu
Image thumbnailing is an essential technique to efficiently visualize large-scale consumer photos or image search results. In this paper, we propose a hierarchical multi-view face detection algorithm for image thumbnailing, and a unified framework which aggregates both the low-level saliency and high-level semantics through detected faces to augment thumbnail generation with the consideration of photography aesthetics. The approach can produce more informative and pleasant thumbnails in comparison with the prior work with limitation representations. We also investigate the effective feature sets and informative feature dimensions for discriminative multi-view face detection.