In this paper, we propose an efficient algorithm for robust place recognition and loop detection using camera information only. Our pipeline purely relies on spatial localization and semantic information of road markings. The creation of the database of road markings sequences is performed online, which makes the method applicable for real-time loop closure for visual SLAM techniques. Furthermo...

Fast binary descriptors build the core for many vision based applications with real-time demands like object detection, Visual Odometry or SLAM. Commonly it is assumed, that the acquired images and thus the patches extracted around keypoints originate from a perspective projection ignoring image distortion or completely different types of projections such as omnidirectional or fisheye. Usually ...

This paper presents a method for extracting distinctive textural features from images taken from natural scenes. The aim is to use natural landmarks for navigation in an unexplored environment. Natural features are all different and complex in shape. To be able to use them for navigation, informative representation of these features and a careful selection process is required. The present metho...

Object detection and tracking its movement is an important aspect in today’s sports broadcasting industry. It helps in post-match analysis, studying previous matches to find drawbacks in one’s technique and also helps in discussion and debate. Detecting a moving object is a cumbersome technique as it involves a very complex human movement as well. In this paper, movement of tennis ball is detec...

This work proposes a new, online algorithm for estimating the local scale correction to apply to the output of a monocular SLAM system and obtain an as faithful as possible metric reconstruction of the 3D map and of the camera trajectory. Within a Bayesian framework, it integrates observations from a deep-learning based generic object detector and a prior on the evolution of the scale drift. Fo...

Among the recent trends in real-time visual SLAM, there has been a move towards the construction of structure-rich maps. By using landmarks more descriptive than point features, such as line or surface segments, larger parts of the scene can be represented in a compact form. This minimises redundancy and might allow applications such as object detection and path planning. In this paper, we prop...

We develop a supervised ranking model to rerank candidates generated from an SMT-based grammatical error correction (GEC) system. A range of novel features with respect to GEC are investigated and implemented in our reranker. We train a rank preference SVM model and demonstrate that this outperforms both Minimum Bayes-Risk and Multi-Engine Machine Translation based re-ranking for the GEC task. ...

Iris localization is a very important approach in biometric identification systems. Identification process usually is implemented in three levels: iris localization, feature extraction, and pattern matching finally. Accuracy of iris localization as the first step affects all other levels and this shows the importance of iris localization in an iris based biometric system. In this paper, we cons...

This paper presents the first study using neural machine translation (NMT) for grammatical error correction (GEC). We propose a twostep approach to handle the rare word problem in NMT, which has been proved to be useful and effective for the GEC task. Our best NMTbased system trained on the CLC outperforms our SMT-based system when testing on the publicly available FCE test set. The same system...

The microfabrication of electrochemical immunosensors for the simultaneous detection of two protein analytes is described. The sensors consisted of two iridium oxide electrodes (1-mm diameter) patterned on a glass substrate. Capture antibodies were immobilized on the porous iridium oxide electrodes by covalent attachment using (3-aminopropyl)triethoxysilane and glutaraldehyde. The spatial separ...