The task of semantic segmentation holds a fundamental position in the field computer vision. Assigning label to each pixel an image is challenging task. In recent times, significant advancements have been achieved through application Convolutional Neural Networks (CNN) techniques based on deep learning. This paper presents comprehensive and structured analysis approximately 150 methods CNN with...

Fig. 1 shows a Free viewpoint TV (FTV) system [7]. FTV can generate very natural free viewpoint images in real time as shown in Fig. 2. A scene is captured using a dense array of synchronized cameras. The camera images are placed in a simple manner forming a Ray Space [8] that allows rendering the scene from any position by simple processing. So the user can view the scene not only from the ori...

In this paper, a feature-based technique for the camera pose estimation in a sequence of wide-baseline images has been proposed. Camera pose estimation is an important issue in many computer vision and robotics applications, such as, augmented reality and visual SLAM. The proposed method can track captured images taken by hand-held camera in room-sized workspaces with maximum scene depth of 3-4...

Automatic category discovery from images is a challenging problem in computer vision community especially from natural scene images due to the great variability in them. This paper proposes a novel context-aware topic model for category discovery in complex natural scenes. The proposed model constructs a generative probabilistic procedure from three-level features consisting of patch, region an...

Land cover is important for global change studies, and its accuracy reliability are usually verified by field sampling, which costs a lot. A method was proposed the verification of land datasets with geo-tagged natural scene images using convolutional neural network. The nature were firstly collected from Use Cover Area frame Survey (LUCAS) crowdsourcing platform Flickr, then classified accordi...

This paper presents a novel approach to natural scene segmentation. It uses both color and texture features in cooperation to provide comprehensive knowledge about every pixel in the image. A novel scheme for the collection of training samples, based on homogeneity, is proposed. Natural scene segmentation is carried out using a two-stage hierarchical self-organizing map (HSOM). The proposed met...

By combining a perceptual discrimination task and a visuospatial working memory task, the present study examined the effects of visuospatial working memory load on the hierarchical processing of scene gist. In the perceptual discrimination task, two scene images from the same (manmade-manmade pairing or natural-natural pairing) or different superordinate level categories (manmade-natural pairin...