This paper proposes a novel MAP inference framework for Markov Random Field (MRF) in parallel computing environments. The inference framework, dubbed Swarm Fusion, is a natural generalization of the Fusion Move method. Every thread (in a case of multi-threading environments) maintains and updates a solution. At each iteration, a thread can generate arbitrary number of solution proposals and tak...

The 2.1D sketch is a layered representation of occluding and occluded surfaces of the scene. Extracting the 2.1D sketch from a single image is a difficult and important problem arising in many applications. We present a fast and robust algorithm that uses boundaries of image regions and T-junctions, as important visual cues about the scene structure, to estimate the scene layers. The estimation...

We consider the task of depth estimation from a single monocular image. We take a supervised learning approach to this problem, in which we begin by collecting a training set of monocular images (of unstructured outdoor environments which include forests, trees, buildings, etc.) and their corresponding ground-truth depthmaps. Then, we apply supervised learning to predict the depthmap as a funct...

Abstract In order to broaden the discussion on safety of bicycle transport, this paper uses analytical capacity spatial syntax applied recording accidents involving cyclists in city Rolândia-PR, located Southern Region Brazil. With availability 535 reports trips made by mode, collected survey origin and destination city, a database was elaborated where each segment road received its numerical v...

Capturing vehicular travel behavior is one of the most popular models that deal with relevant aspects of urban regions and communities. Since 1960s, it has been matured and evolved to cover all aspects of travel demand applications. Different theories are employed to predict the movement of trip makers’ likewise metric method and the estimation of origin-destination matrixes, intervening opport...