Isotropic Granularity-tunable gradients partition (IGGP) descriptors for human detection

This paper presents a new descriptor for human detection in still images. It is referred to as isotropic granularity-tunable gradients partition (IGGP), which is extended from granularity-tunable gradients partition (GGP) descriptors. The isotropic representation is achieved by aligning the features with different orientation channels according to their principal angles. The benefits of this extension are two folds: firstly, since the partitions' sizes of all the orientation channels are equal, the noise introduce by the small partitions in the original GGP descriptors is eliminated and the performance can be essentially improved; secondly, the integral image based fast computation is applied and more than 20 times speedup has been achieved. In addition, we introduce a new human dataset HIMA. Unlike the previous available human datasets which are mainly captured on the street views for automobile safety or robotics, HIMA dataset is captured on the outdoor work fields for industry...

• Type: Journal
• Year: 2010
• Where: BMVC
• Authors: Yazhou Liu, Janne Heikkilä
• Keywords: BMVC 2010, Computer Vision, Granularity-tunable Gradients Partition, Human Datasets, Orientation Channels