Abstract:
A framework is proposed to generate datasets good for benchmarking face detection using database meant for benchmarking face recognition. Instead of the common way of col...Show MoreMetadata
Abstract:
A framework is proposed to generate datasets good for benchmarking face detection using database meant for benchmarking face recognition. Instead of the common way of collecting images manually, the datasets from the proposed framework are made by a synthesis process with two phases: intrinsic parameterization and extrinsic parameterization. The former parameterizes the intrinsic variables that affect the appearance of a face, while the latter parameterizes the extrinsic variables that dominate how faces appear on background images as required by a test criterion. Experiments reveal that the proposed framework can generate test samples similar to those available from a popular face detection database, and also samples unavailable from existing face databases.
Published in: 2010 IEEE International Conference on Image Processing
Date of Conference: 26-29 September 2010
Date Added to IEEE Xplore: 03 December 2010
ISBN Information: