Eye movements are an external manifestation of selective attention and can play an important role in indicating which attributes of a scene carry the most pertinent information. Models that predict gaze distribution often define a local conspicuity value that relies on low-level image features to indicate the perceived salience of an image region. While such bottom-up models have some success i...

Observers can generally make reliable judgments of surface color in natural scenes despite changes in an illuminant that is out of view. This ability has sometimes been attributed to observers' estimating the spectral properties of the illuminant in order to compensate for its effects. To test this hypothesis, two surface-color-matching experiments were performed with images of natural scenes o...

Early stages of visual processing may exploit the characteristic structure of natural visual stimuli. This structure may differ from the intrinsic structure of natural scenes, because sampling of the environment is an active process. For example, humans move their eyes several times a second when looking at a scene. The portions of a scene that fall on the fovea are sampled at high spatial reso...

This paper proposes a method for detecting changes of a scene using a pair of its vehicular, omnidirectional images. Previous approaches to the problem require the use of a 3D scene model and/or pixel-level registration between different time images. They are also computationally costly for estimating city-scale changes. We propose a novel change detection method that uses features of convoluti...

Holistic representations of natural scenes is an effective and powerful source of information for semantic classification and analysis of arbitrary images. Recently, the frequency domain has been successfully exploited to holistically encode the content of natural scenes in order to obtain a robust representation for scene classification. In this paper, we present a new approach to naturalness ...

Expressing mental images visually as 3D scenes is a time-consuming challenge. Therefore, we employ natural language to facilitate the creation of virtual environments. In this paper, we present a framework, which automatically converts an arbitrary descriptive text into a representative 3D scene. Our system parses a user-written input text, extracts information using techniques from Natural Lan...

With the development of multimedia technology and computer network, the number of available images increases with an explosive speed. But the technology also brings some trouble to its users, sometimes it’s very difficult for us to find some details that very important from a huge amount of available data. At this time, image scene and emotion categorization technologies are required urgently. ...

With the rapid growth of camera-based mobile devices, applications that answer questions such as, “What does this sign say?" are becoming increasingly popular. This is related to the problem of optical character recognition (OCR) where the task is to recognize text occurring in images. The OCR problem has a long history in the computer vision community. However, the success of OCR systems is la...

Image understanding by computer is advancing exponentially these days due to the phenomenal success of deep learning, but there is still much work left for the computers to reach human level perception. Image classification (sometimes with localization) is one of the standard task, but this is far from the image understanding. The other tasks such as image caption generation or visual question ...