Extracting text character from natural scene images is a challenging problem due to differences in text style, font, size, orientation, alignment and complex background. The text data present in images and video contain certain useful information for content-based information indexing and retrieval, sign translation and intelligent driving assistance. In scene text extraction, adjacent characte...

This paper introduces a novel method for generating an intermediate view of soccer scene taken by multiple video cameras. In the proposed method, soccer scene is classified into dynamic regions, a field region, and a background region. Using epipolar geometry in the first region and homography in the second, dense correspondence is obtained to interpolate views. For the third region, partial ar...

During natural vision, humans categorize the scenes they encounter: an office, the beach, and so on. These categories are informed by knowledge of the way that objects co-occur in natural scenes. How does the human brain aggregate information about objects to represent scene categories? To explore this issue, we used statistical learning methods to learn categories that objectively capture the ...

Recognition of human actions is usually addressed in the scope of video interpretation. Meanwhile, common human actions such as “reading a book”, “playing a guitar” or “writing notes” also provide a natural description for many still images. In addition, some actions in video such as “taking a photograph” are static by their nature and may require recognition methods based on static cues only. ...

We propose a perceptual fog density prediction model based on natural scene statistics (NSS) and “fog aware” statistical features, which can predict the visibility in a foggy scene from a single image without reference to a corresponding fogless image, without side geographical camera information, without training on human-rated judgments, and without dependency on salient objects such as lane ...

Scene perception is a fundamental aspect of vision. Humans are capable of analyzing behaviorally-relevant scene properties such as spatial layouts or scene categories very quickly, even from low resolution versions of scenes. Although humans perform these tasks effortlessly, they are very challenging for machines. Developing methods that well capture the properties of the representation used by...

Localizing text regions in images taken from natural scenes is one of the challenging problems dueto variations in font, size, color and orientation of text. In this paper, we introduce a new concept socalled Edge Color Signature for localizing text regions in an image. This method is able to localizeboth Farsi and English texts. In the proposed method rst a pyramid using diff...

Manuscript received July 12,1982; revised April 20, 1983. This work was supported by the Defense Advanced Research Projects Agency, ARPA Order 3597, monitored by the U.S. Air Force Avionics Labora tory under Contract F33615 -81-K-1539. M. Herman and T. Kanade are with thc Department o f Computer Science, Carnegie -Mellon University, Pittsburgh, PA 15213. S. Kuroe was on leave at the Robotics In...

An end-to-end method for multi-language scene text localization, recognition and script identification is proposed. The approach is based on a set of convolutional neural nets. The method, called E2E-MLT, achieves state-of-theart performance for both joint localization and script identification in natural images and in cropped word script identification. E2E-MLT is the first published multi-lan...