We propose a scene classification method, which combines two popular methods in the literature: Spatial Pyramid Matching (SPM) and probabilistic Latent Semantic Analysis (pLSA) mod...
Abstract--Context plays a valuable role in any image understanding task confirmed by numerous studies which have shown the importance of contextual information in computer vision t...
Sobhan Naderi Parizi, Ivan Laptev, Alireza Tavakol...
Semantic scene classification is a useful, yet challenging problem in image understanding. Most existing systems are based on low-level features, such as color or texture, and suc...
Matthew R. Boutell, Anustup Choudhury, Jiebo Luo, ...
Classifying natural scenes into semantic categories has always been a challenging task. So far, many works in this field are primarily intended for single label classification, wh...
Prior research in scene classification has shown that high-level information can be inferred from low-level image features. Classification rates of roughly 90% have been reported ...
Semantic scene classification is an open problem in image understanding, especially when information purely from image content (i.e., pixels) is employed. However, in applications...
Given a set of images of scenes containing multiple object categories (e.g. grass, roads, buildings) our objective is to discover these objects in each image in an unsupervised man...
Classifying pictures into one of several semantic categories is a classical image understanding problem. In this paper, we present a stratified approach to both binary (outdoor-in...