Semantic annotation for complex video street views based on 2D–3D multi-feature fusion and aggregated boosting decision forests
作者：
Highlights：
• 2D and 3D superpixel features for object representation.
• A modified aggregated boosting decision forest for fast and accurate classification.
• Only a small amount of samples for building classification model.
• An effective tool for accurate and efficient semantic annotation of complex street views.
• Better performance in accuracy, robustness and computation efficiency.
摘要
Highlights•2D and 3D superpixel features for object representation.•A modified aggregated boosting decision forest for fast and accurate classification.•Only a small amount of samples for building classification model.•An effective tool for accurate and efficient semantic annotation of complex street views.•Better performance in accuracy, robustness and computation efficiency.
论文关键词：Semantic annotation,Superpixel segmentation,2D–3D feature fusion,ABDF model
论文评审过程：Received 1 December 2015, Revised 8 July 2016, Accepted 24 August 2016, Available online 30 August 2016, Version of Record 19 September 2016.
论文官网地址：https://doi.org/10.1016/j.patcog.2016.08.030
