Addressing Challenging Place Recognition Tasks using Generative Adversarial Networks

Place recognition is an essential component of Simultaneous Localization And Mapping (SLAM). Under severe appearance change, reliable place recognition is a difficult perception task since the same place is perceptually very different in the morning, at night, or over different seasons. This work addresses place recognition as a domain translation task. Using a pair of coupled Generative Adversarial Networks (GANs), we show that it is possible to generate the appearance of one domain (such as summer) from another (such as winter) without requiring image-to-image correspondences across the domains. Mapping between domains is learned from sets of images in each domain without knowing the instance-to-instance correspondence by enforcing a cyclic consistency constraint. In the process, meaningful feature spaces are learned for each domain, the distances in which can be used for the task of place recognition. Experiments show that learned features correspond to visual similarity and can be effectively used for place recognition across seasons.Comment: Accepted for publication in IEEE International Conference on Robotics and Automation (ICRA), 201

Comparative assessment of HDI with Composite Development Index (CDI)

International audienceThis paper presents a novel approach to measure the human development, progress and growth of any country. The authors have developed an alternative index to the conventional 'HDI', named as 'Composite Development Index (CDI)' and have also presented an original approach to evaluate it quantitatively. The CDI integrates all the three (social, economic and environmental) aspects of sustainable development, along with peace and happiness. As proposed, the CDI is based on four parameters, i.e. Inequality adjusted HDI (IHDI), Scaled Green Index, Scaled Peace Index and Scaled Happiness Index, evaluated from globally accepted standard databases. Hence, the CDI is much more comprehensive and rational than the conventional HDI or GDP. The CDI values have been evaluated quantitatively for 126 countries of the world. Further, comparative assessment of the CDI has been done with the HDI for all the 126 nations. The results obtained have been startling as no country was even able to have a CDI score of 0.8 on a scale of 0.1 to 1. Switzerland had the highest CDI of 0.767. A country like Norway with the highest HDI of 0.953 had a CDI of only 0.742. On the other hand, countries like Costa Rica, Romania and Uruguay are in the top 20 nations in the CDI Ranking, much ahead of the countries like United Kingdom, France, and USA. The CDI can act as a single point of reference for policy-makers, governments and other development agencies, as it presents a consolidated picture of a country's development. Future course of action on the basis of the concept of CDI are also proposed. It can be concluded that efforts to have a high CDI (in comparison to a high GDP or HDI only) will pave the way forward for sustainable development and holistic progress for all the countries of the world. JEL Classifications: 011, 015 Additional disciplines (besides field of economics reflected in JEL classifications): sociology; ecology and environment

A polylogarithmic approximation algorithm for group Steiner tree problem

The group Steiner tree problem is a generalization of the Steiner tree problem where we are given several subsets (groups) of vertices in a weighted graph, and the goal is to find a minimum-weight connected subgraph containing at least one vertex from each group. The problem was introduced by Reich and Widmayer and finds applications in VLSI design. The group Steiner tree problem generalizes the set covering problem, and is therefore at least as hard. We give a randomized $O(\log^3 n \log k)$-approximation algorithm for the group Steiner tree problem on an $n$-node graph, where $k$ is the number of groups.The best previous performance guarantee was $(1+\frac{\ln k}{2})\sqrt{k}$ (Bateman, Helvig, Robins and Zelikovsky). Noting that the group Steiner problem also models the network design problems with location-theoretic constraints studied by Marathe, Ravi and Sundaram, our results also improve their bicriteria approximation results. Similarly, we improve previous results by Slav{\'\i}k on a tour version, called the errand scheduling problem. We use the result of Bartal on probabilistic approximation of finite metric spaces by tree metrics to reduce the problem to one in a tree metric. To find a solution on a tree, we use a generalization of randomized rounding. Our approximation guarantees improve to $O(\log^2 n \log k)$ in the case of graphs that exclude small minors by using a better alternative to Bartal's result on probabilistic approximations of metrics induced by such graphs (Konjevod, Ravi and Salman) -- this improvement is valid for the group Steiner problem on planar graphs as well as on a set of points in the 2D-Euclidean case

Computed tomography guided fine needle aspiration cytology of thoracic lesions: 10 year experience of an interventional pulmonologist

Background: Diagnosis of thoracic lesions may be challenging, due to various factors associated with the lesion and subsequent invasive investigations. Computed tomography guided fine needle aspiration cytology (CT-guided FNAC) is a minimally invasive method for thoracic lesions considered non approachable by other modalities.Methods: Retrospective analysis of patients subjected to CT-guided FNAC during year 2004 to 2014 was done. In these patients, non-invasive and invasive methods like fibre-optic bronchoscopy/ ultrasound guided FNAC were inconclusive/ expected to be inconclusive. Records were statistically analyzed for patient related, lesion related and procedure related factors, and their effect on yield and complications.Results: 435 patients underwent CT-guided FNAC. Age ranged from 10 to 95 years, with male preponderance. Diagnostic yield was 80.2%. Neoplastic lesions (255/435 (58.6%)) were most commonly diagnosed with majority (206/255 (80.8%)) being non-small cell lung cancer (NSCLC). This was followed by non-neoplastic lesions (94/435 (21.6%)) with Tuberculosis (42/94(44.7%)) being most common in this group. In 227/435 patients, other details like side and size of the lesion, position of patient during the procedure, depth of lesion from skin surface, number of passes undertaken and complications, if any, were also available. They were separately analyzed. Mean size of lesion was 5.7575 X 5.4173cms (maximum vertical X maximum horizontal diameter). Mean depth to which needle was inserted was 5.6663cms. Mean number of passes per patient were 1.98. Right sided lesions were more commonly sampled than left. Supine positioning was most commonly employed. Overall complication rate was 4% (9/227).Conclusions: CT-guided FNAC for thoracic lesions can serve as early diagnostic tool and guide in planning effective management strategies

TIME AND LOCATION FORENSICS FOR MULTIMEDIA

In the modern era, a vast quantities of digital information is available in the form of audio, image, video, and other sensor recordings. These recordings may contain metadata describing important information such as the time and the location of recording. As the stored information can be easily modified using readily available digital editing software, determining the authenticity of a recording has utmost importance, especially for critical applications such as law enforcement, journalism, and national and business intelligence. In this dissertation, we study novel environmental signatures induced by power networks, which are known as Electrical Network Frequency (ENF) signals and become embedded in multimedia data at the time of recording. ENF fluctuates slightly over time from its nominal value of 50 Hz/60 Hz. The major trend of fluctuations in the ENF remains consistent across the entire power grid, including when measured at physically distant geographical locations. We investigate the use of ENF signals for a variety of applications such as estimation/verification of time and location of a recording's creation, and develop a theoretical foundation to support ENF based forensic analysis. In the first part of the dissertation, the presence of ENF signals in visual recordings captured in electric powered lighting environments is demonstrated. The source of ENF signals in visual recordings is shown to be the invisible flickering of indoor lighting sources such as fluorescent and incandescent lamps. The techniques to extract ENF signals from recordings demonstrate that a high correlation is observed between the ENF fluctuations obtained from indoor lighting and that from the power mains supply recorded at the same time. Applications of the ENF signal analysis to tampering detection of surveillance video recordings, and forensic binding of the audio and visual track of a video are also discussed. In the following part, an analytical model is developed to gain an understanding of the behavior of ENF signals. It is demonstrated that ENF signals can be modeled using a time-varying autoregressive process. The performance of the proposed model is evaluated for a timestamp verification application. Based on this model, an improved algorithm for ENF matching between a reference signal and a query signal is provided. It is shown that the proposed approach provides an improved matching performance as compared to the case when matching is performed directly on ENF signals. Another application of the proposed model in learning the power grid characteristics is also explicated. These characteristics are learnt by using the modeling parameters as features to train a classifier to determine the creation location of a recording among candidate grid-regions. The last part of the dissertation demonstrates that differences exist between ENF signals recorded in the same grid-region at the same time. These differences can be extracted using a suitable filter mechanism and follow a relationship with the distance between different locations. Based on this observation, two localization protocols are developed to identify the location of a recording within the same grid-region, using ENF signals captured at anchor locations. Localization accuracy of the proposed protocols are then compared. Challenges in using the proposed technique to estimate the creation location of multimedia recordings within the same grid, along with efficient and resilient trilateration strategies in the presence of outliers and malicious anchors, are also discussed