Co-occurrence Histograms of Oriented Gradients for Pedestrian Detection

By Tomoki Watanabe, Satoshi Ito, Kentaro Yokoi. 2009

271 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Xiaogang Wang
2. Luc Van Gool
3. Bernt Schiele
4. Wanli Ouyang
5. Dacheng Tao
6. Yi Yang
7. Jitendra Malik
8. Trevor Darrell

Citations in the corpus

• Boosted local structured HOG-LBP for object localization (2011, background): “During the past few years, many variants of HOG have been presented, such as Co-occurrence Histograms of Oriented Gradients(CoHOG) [26] in which the co-occurrence with various positional offsets is adopted to express complex shapes of object.”
• New features and insights for pedestrian detection (2010, background): “Furthermore, second order image statistics, especially co-occurrence histograms, are gaining popularity, pushing feature spaces to extremely high dimensions [25, 18].”
• Face recognition using Histograms of Oriented Gradients (2011, background): “…used in many different problems in computer vision, such as pedestrian detection (Bertozzi et al., 2007; Wang and Lien, 2007; Chuang et al., 2008; Watanabe et al., 2009; Baranda et al., 2008; He et al., 2008; Kobayashi et al., 2008; Suard et al., 2006; Zhu et al., 2006; Perdersoli et al.,…”