Classifying Street Spaces with Street View Images for a Spatial Indicator of Urban Functions

Layered Interpretation of Street View Images

We propose a layered street view model to encode both depth and semantic information on street view images for autonomous driving. Recently, stixels, stix-mantics, and tiered scene labeling methods have been proposed to model street view images. We propose a 4-layer street view model, a compact representation over the recently proposed stix-mantics model. Our layers encode semantic classes like...

Entrance Detection from Street-View Images

We present a system for detecting building entrances in outdoor scenes, an important problem for urban scene understanding. While entrance detection in indoor scenes has received a lot of attention, tackling the problem in outdoor scenes is considerably more complicated and remains largely unexplored. The wide variety of door appearances and geometries, background clutter, occlusions, speculari...

Building Instance Classification Using Street View Images

This is the pre-print version, to read the final version please go to ISPRS Journal of Photogrammetry and Remote Sensing, Elsevier. (https://doi.org/DOI: 10.1016/j.isprsjprs.2018.02.006). Land-use classification based on spaceborne or aerial remote sensing images has been extensively studied over the past decades. Such classification is usually a patch-wise or pixel-wise labeling over the whole...

Estimating Height and Diameter Growth of Some Street Trees in Urban Green Spaces

Estimating urban trees growth, especially tree height is very important in urban landscape management. The aim of the study was to predict of tree height base on tree diameter. To achieve this goal, 921 trees from five species were measured in five areas of Mashhad city in 2014. The evaluated trees were ash tree (Fraxinus species), plane tree (Platanus hybrida), white mulberry (Morus alba), ail...

Improving the Quality of Urban Spaces through Image Processing, Case Study: 17th-Shahrivar Street of Tehran