There has been a growing interest in exploiting contextual information in addition to local features to detect and localize multiple object categories in an image. Context models can efficiently rule out some unlikely combinations or locations of objects and guide detectors to produce a semantically coherent interpretation of a scene. However, the performance benefit from using context models has been limited because most of these methods were tested on datasets with only a few object categories, in which most images contain only one or two object categories. In this paper, we introduce a new dataset with images that contain many instances of different object categories and propose an efficient model that captures the contextual information among more than a hundred of object categories. We show that our context model can be applied to scene understanding tasks that local detectors alone cannot solve.
The context of an image encapsulates rich information about how natural scenes and objects are related to each other. Such contextual information has the potential to enable a coherent understanding of natural scenes and images. However, context models have been evaluated mostly based on the improvement of object recognition performance even though it is only one of many ways to exploit contextual information. In this paper, we present a new scene understanding problem for evaluating and applying context models. We are interested in finding scenes and objects that are "out-of-context". Detecting "out-of-context" objects and scenes is challenging because context violations can be detected only if the relationships between objects are carefully and precisely modeled. To address this problem, we evaluate different sources of context information, and present a graphical model that combines these sources. We show that physical support relationships between objects can provide useful contextual information for both object recognition and out-of-context detection.
Aloe has been widely used in phytomedicine. Phytomedicine describes aloe as a herb which has anti-inflammatory, anti-proliferative, anti-aging effects. In recent years several cases of aloe-induced hepatotoxicity were reported. But its pharmacokinetics and toxicity are poorly described in the literature. Here we report three cases with aloe-induced toxic hepatitis. A 57-yr-old woman, a 62-yr-old woman and a 55-yr-old woman were admitted to the hospital for acute hepatitis. They had taken aloe preparation for months. Their clinical manifestation, laboratory findings and histologic findings met diagnostic criteria (RUCAM scale) of toxic hepatitis. Upon discontinuation of the oral aloe preparations, liver enzymes returned to normal level. Aloe should be considered as a causative agent in hepatotoxicity.
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