戶外停車場空位自動偵測系統

Abstract

在本計畫中，我們提出了一套停車場空位偵測系統。與一般以車輛偵測導向或是空位偵測導向的方法不同，我們是以停車場為導向。在我們系統中，我們將停車場視為多平面組成的架構。在這樣的架構中，為了推論空車位，我們提出了一套基於表面階層的架構，整合三度空間資訊與區塊式的影像觀測。為了增強系統穩定性，我們使用Histogram of Oriented Gradients (HOG)進行區塊的特徵向量擷取。將這樣的特徵向量整合至系統中，我們可以有效的透過最佳化推論停車場的狀態，特別是針對一些困難的處理情況如遮蔽現象，光影問題，三度空間失真問題以及光照狀況不佳的白天或是夜晚情形。

We proposed a surface-based vacant parking space detection system. Unlike many car-oriented or space-oriented methods, the proposed system is parking-lot-oriented. In the system, we treat the whole parking lot as a structure consisting of plentiful surfaces. A surface-based hierarchical framework is then proposed to integrate the 3-D scene information with the patch-based image observation for the inference of vacant space. To be robust, the feature vector of each image patch is extracted based on the Histogram of Oriented Gradients (HOG) approach. By incorporating these texture features into the proposed probabilistic models, we could systematically infer the optimal hypothesis of parking statuses while dealing with occlusion effect, shadow effect, perspective distortion, and fluctuation of lighting condition in both day time and night time.