Semantically complex queries which include attributes of objects and relations between objects still pose a major challenge to image retrieval systems. Recent work in computer vision has shown that a graph-based semantic representation called a scene graph is an effective representation for very detailed image descriptions and for complex queries for retrieval. In this paper, we show that scene...

We consider the potential implications of recent developments in subfields of image analysis and image representation for watermarking and steganography. We consider three rapidly developing subfields: 1. Natural Scene Statistics; 2. Level Set Image Processing and Geometric Diffusion; and 3. Computational Harmonic Analysis. Each of these subfields has recently claimed progress either in charact...

Introduction: In order to recognize the image of a natural scene, coherent patterns should be extracted and processed separately for reducing the complexity of the problem, because several objects usually exist in a natural scene. D. L. Wang et al. proposed a nonlinear oscillator network model called locally excitatory, globally inhibitory oscillator networks (LEGION) for image segmentation [1]...

Image Processing play on vital role an enhanced image or to extract some useful information from it. It is a type of signal dispensation in which input is image like video frame or photograph. Text character and strings in natural scene can provide valuable information for more applications. Retrieving text directly from natural scene image or video is challenging task because of diverse text p...

In this paper, we introduce a new method for depth perception from a 2D natural scene using scale variation of patterns. As the surface from a 2D scene gets farther away from us, the texture appears finer and smoother. Texture gradient is one of the monocular depth cues which can be represented by gradual scale variations of textured patterns. To extract feature vectors from textured patterns, ...

To truly understand the visual world our models should be able not only to recognize images but also generate them. To this end, there has been exciting recent progress on generating images from natural language descriptions. These methods give stunning results on limited domains such as descriptions of birds or flowers, but struggle to faithfully reproduce complex sentences with many objects a...

Natural scene features stabilize and extend the tracking range of augmented reality (AR) pose-tracking systems. We develop robust computer vision methods to detect and track natural features in video images. Point and region features are automatically and adaptively selected for properties that lead to robust tracking. A multistage tracking algorithm produces accurate motion estimates, and the ...

We present a process for estimating spatially-varying surface reflectance of a complex scene observed under natural illumination conditions. The process uses a laser-scanned model of the scene’s geometry, a set of digital images viewing the scene’s surfaces under a variety of natural illumination conditions, and a set of corresponding measurements of the scene’s incident illumination in each ph...

In a contextual cuing paradigm, we examined how memory for the spatial structure of a natural scene guides visual search. Participants searched through arrays of objects that were embedded within depictions of real-world scenes. If a repeated search array was associated with a single scene during study, then array repetition produced significant contextual cuing. However, expression of that lea...