Abstract

Reconstructing geometric models of relief carv-ings are of great importance in preserving cultural heritages digitally. In case of reliefs, using laser scanners and structured lighting techniques is not always feasible or are very expensive given the uncontrolled environment. Single image shape from shading is an under-constrained problem that tries to solve for the surface normals given the intensity image. Various constraints are used to make the problem tractable. To avoid the uncontrolled lighting, we use a pair of images with and without the flash and compute an image under a known illumination.This image is used as an input to the shape reconstruction algorithms. We present techniques that try to reconstruct theshape from relief images using the prior information learned from examples. We learn the variations in geometric shape corresponding to image appearances under different lighting conditions using sparse representations. Given a new image,we estimate the most appropriate shape that will result in the given appearance under the specified lighting conditions. We integrate the prior with the normals computed from reflectance equation in a MAP framework. We test our approach on relief images and compare them with the state-of-the-art shape from shading algorithms.

Abstract

n this paper we present a max-flow min-cut based salient object detection in 3D point cloud that results from Struc-ture from Motion (SfM) pipeline. The SfM pipeline generates noisy point cloud due to the unwanted scenes captured along with the object in the image dataset of SfM. The background points being sparse and not meaningful, it becomes necessary to remove them. Hence, any further processes (like surface reconstruction)utilizing the cleaned up model will have no hinderance from the noise removed. We present a novel approach where the camera centers are used to segment out the salient object. The algorithm is completely autonomous and does not need any user input. We test our proposed method on Indian historical models reconstructed through SfM. We evaluate the results in terms of selectivity and specificity.

Abstract

his paper addresses the problem of reconstruction of specular surfaces using a combination of Dynamic Program­ming and Markov Random Fields formulation. Unlike traditional methods that require the exact position of environment points to be known, our method requires only the relative position of the environment points to be known for computing approximate normals and infer shape from them. We present an approach which estimates the depth from dynamic programming routine and MRF stereo matching and use MRF optimization to fuse the results to get the robust estimate of shape. We used smooth color gradient image as our environment texture so that shape can be recovered using just a single shot. We evaluate our method using synthetic experiments on 3D models like Stanford bunny and show the real experiment results on golden statue and silver coated statue.

Abstract

Online debate forums provide a rich collection of differing opinions on various topics. In dual-sided debates, users present their opinions or judge other’s opinions to support their stance. In this paper, we examine the use of users’ intentions and debate structure for stance classification of the debate posts. We propose a domain independent approach to capture users’ intent at sentence level using its dependency parse and sentiWordNet and to build the intention structure of the post to identify its stance. To aid the task of classification, we define the health of the debate structure and show that maximizing its value leads to better stance classification accuracies.

Abstract

Mangroves are high productive estuarine ecosystem, protect barrage and defend the impact of big storms. Numerous studies attempted to map the locations of mangroves and analyse changes using different sensors including optical sensors: LANDSAT, IRS, SPOT, and other from past four decades. The present work attempts to identify the mangroves at species level using high resolution remote sensing data with field based measurements. The lack of spatial quantitative mangroves maps for the west coast has led to overlooking of the importance of mangroves and also the implementation of restoration programmes. Mangroves planting in the small estuaries of the Uttara Kannada district of Karnataka State during the recent years have yielded desired results of better ecology and higher biological production. The RS data using 2010 IRS p6 L4 MX having resolution of 5 M is useful in mapping the distribution of adult mangroves. However for mapping juveniles and shrubby forms require higher spectral resolution data. Using open source GIS software (QGIS) and remote sensing software (GRASS) and IRS imageries mangrove areas and potential areas available for planting in three river estuaries in the Honnavar Forest Division of Uttara Kannada were mapped. Mangrove species are recommended for planting in suitable areas based on salinity regimes. The effective forest management in the region shows mangroves have expanded in several regions due to the conservation measures and supervision. The net gain in mangroves could be attributed to new plantations by the State Forest Department and effective protection; agriculture to mangroves; mudflat to mangroves. The overall accuracy of satellite imagery processing was 90.89% and the Kappa index was 0.89. The work demonstrates the potential of high resolution multi-temporal satellite remote sensing data with ground based measurements for effective mapping mangrove forests in coastal regions.

Abstract

Social networking sites provide users a virtual community interaction platform to share their thoughts, life experiences and opinions. Online debate forum is one such platform where people can take a stance and argue in support or opposition of debate topics. An important feature of such forums is that, they are dynamic and increase rapidly. In such situations, e↵ective opinion summarization approaches are needed so that readers need not go through the entire debate. This paper aims to summarize online debates by extracting highly topic relevant and sentiment rich sentences. The proposed approach takes into account topic relevant, document relevant and sentiment based features to capture topic opinionated sentences. ROUGE scores are used to evaluate our system. Our system significantly outperforms several baseline systems and show 5.2% (ROUGE-1), 7.3%(ROUGE-2) and 5.5% (ROUGE-L) improvement over the state-of-the-art opinion summarization system. The results verify that topic directed sentiment features are most important to generate e↵ective debate summaries.

Abstract

This paper presents a novel approach to categorize, model and identify contextual information in natural language interface to database (NLIDB) systems. The interactions between user and system are categorized and modeled based on the way in which the contextual information is utilized in the interactions. A relationship schema among the responses (user and system responses) is proposed. We present a novel method to identify contextual information in one specific type of usersystem interaction. We report on results of experiments with the university related queries.

Abstract

In studies like change analysis, the availability of very high resolution (VHR)/high resolution (HR) imagery for a particular period and region is a challenge due to the sensor revisit times and high cost of acquisition. Therefore, most studies prefer lower resolution (LR) sensor imagery with frequent revisit times, in addition to their cost and computational advantages. Further, the classification techniques provide us a global estimate of the class accuracy, which limits its utility if the accuracy is low. In this work, we focus on the sub-classification problem of LR images and estimate regions of higher confidence than the global classification accuracy within its classified region. The spectrally classified data was mined into spatially clustered regions and further refined and processed using statistical measures to arrive at local high confidence regions (LHCRs), for every class. Rabi season MODIS data of January 2006 & 2007 …

Abstract

Land use and land cover (LULC) changes induced by human or natural processes drive biogeochemistryof the Earth influencing the climate at global as well as regional scales. Drastic changes in the land cover with the decline in vegetation and water bodies due to anthropogenic activities enhances the heat emission from land surface and atmospheric temperatures Increased land surface temperature (LST) is mainly due to increase in concentrated human activities, paved land cover or barren lands. Due to complexity of landscapes the sampling was difficult to derive LST and environmental response relationships. Temporal data acquired through space borne remote sensors has bridged the gap of temporal data for the entire earth surface. The current study explores the relation between surface biophysical parameters to sub-pixel thermal variations. The thermal infrared bands of remote sensing data help to retrieve LST, which are supplemented byground based measurements. Analysis of LST with LULC indicates a negative correlation between vegetation indices and LST. The general trend in the ambient temperature of Uttara Kannada over the 31 year period was established. Itclarifies that there was a fundamental drift of temperature rise in recent years, especially during the last decade.

Abstract

: Railway is the largest undertaking in the country. A retrospective study of prevailing conditions is necessary to assimilate the progress of the sector and how far have the changes introduced in previous few years been successful. The paper examines how the proposed changes in the Indian railways have changed the face of it through rigorous spatial analysis in diversified fields. A balanced analysis of shortcomings as well as achievements has been tried to be achieved through this paper for few selected regions of India.Each year there has to be more emphasis on enhancing the services provided. The rail budgets play a vital role and are responsible for taking care of it. The numerous promises made in terms of introduction of trains, electrification of routes, gauge conversion, doubling and increasing frequency of trains are made every year, in order to keep track of fulfillment of those decisions the spatial analysis is conducted rigorously. Railway has also witnessed a number of disasters in past few years; the spatial analysis conducted brings out few major reasons of those. A section of study also covers the topographic conditions in the state of Jammu and Kashmir that have not allowed the progress of railways in these regions.