We formulate PRNU-based image manipulation localization as a probabilistic binary labeling task in a flexible discriminative random field (DRF) framework. A novel local discriminator based on the deviation of the measured correlation from the expected local correlation as estimated by a correlation predictor is paired with an explicit pairwise model for dependencies between local decisions. Exp...

Markov networks (MNs) are a powerful way to compactly represent a joint probability distribution, but most MN structure learning methods are very slow, due to the high cost of evaluating candidates structures. Dependency networks (DNs) represent a probability distribution as a set of conditional probability distributions. DNs are very fast to learn, but the conditional distributions may be inco...

In this study, we introduce a new cosegmentation approach, MOMI-cosegmentation, to segment multiple objects that repeatedly appear among multiple images. The proposed approach tackles a more general problem than conventional cosegmentation methods. Each of the shared objects may even appear more than one time in one image. The key idea of MOMI-cosegmentation is to incorporate a common pattern d...

The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In th...

To achieve efficient traffic flow, it is important to base control of traffic signals on observation of pedestrian flow as well as vehicle flow. In consideration of safety, it is also important to analyze behavioral relationship between pedestrians and vehicles, which can be conductive to accidents at intersections. Toward the goals of efficiency and safety, we developed a precise tracking algo...

We extend the validity of the implication of a local limit theorem from an integral one. Our extension eliminates the finite range assumption present in the previous works by using the cluster expansion to analyze the contribution from the tail of the potential. 1. Definitions and Results 1.1. Assumptions We consider a v-dimensional lattice spin system, to each χeZ is associated a spin sx that ...

Considerable effort has been made to increase the scale of Linked Data. However, an inevitable problem when dealing with data integration from multiple sources is that multiple different sources often provide conflicting objects for a certain predicate of the same real-world entity, so-called object conflicts problem. Currently, the object conflicts problem has not received sufficient attention...

In this paper, we present an example-based approach for automatically generating a life-like portrait from a frontal face image. Based on an inhomogeneous Markov Random Field Model, an inhomogeneous non-parametric sampling scheme is used to capture the complex statistical characteristics of face image and corresponding portrait. In our approach, only those pixels corresponding to a portrait poi...