Search results for " image processing."
showing 10 items of 2265 documents
Indoor Space Classification Using Cascaded LSTM
2020
Author's accepted manuscript. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Indoor space classification is an important part of localization that helps in precise location extraction, which has been extensively utilized in industrial and domestic domain. There are various approaches that employ Bluetooth Low Energy (BLE), Wi-Fi, magnetic field, object detecti…
Tracking Hands in Interaction with Objects: A Review
2017
Markerless vision-based 3D hand motion tracking is a key and popular component for interaction studies in many domains such as virtual reality and natural human-computer interfaces. While this research field has been well studied in the last decades, most approaches have considered the human hand in isolation and not in action or in interaction with the environment or the other articulated human body parts. Employing contextual information about the surrounding environment (e.g. the shape, the texture, and the posture of the object in the hand) can remarkably constrain the tracking problem. The goal of this survey is to develop an up-to-date taxonomy of existing vision-based hand tracking m…
An Improved Skew Angle Detection and Correction Technique for Historical Scanned Documents Using Morphological Skeleton and Progressive Probabilistic…
2017
International audience; Skew detection is a crucial step for document analysis systems. Indeed, it represents one of the basic challenges, especially in case of historical documents analysis. In this paper, we propose a novel robust skew angle detection and correction technique. Morphological Skeleton is introduced to significantly reduce the amount of data to treat by removing the redundant pixels and keeping only the central curves of the image components. The proposed method then uses Progressive Probabilistic Hough Transform (PPHT) to identify image lines. A special procedure is finally applied in order to estimate the global skew angle of the document image from these detected lines. E…
Intent Detection System Based on Word Embeddings
2018
Intent detection is one of the main tasks of a dialogue system. In this paper we present our intent detection system that is based on FastText word embeddings and neural network classifier. We find a significant improvement in the FastText sentence vectorization. The results show that our intent detection system provides state-of-the-art results on three English datasets outperforming many popular services.
Visual Marker Guided Point Cloud Registration in a Large Multi-Sensor Industrial Robot Cell
2018
This paper presents a benchmark and accuracy analysis of 3D sensor calibration in a large industrial robot cell. The sensors used were the Kinect v2 which contains both an RGB and an IR camera measuring depth based on the time-of-flight principle. The approach taken was based on a novel procedure combining Aruco visual markers, methods using region of interest and iterative closest point. The calibration of sensors is performed pairwise, exploiting the fact that time-of-flight sensors can have some overlap in the generated point cloud data. For a volume measuring 10m × 14m × 5m a typical accuracy of the generated point cloud data of 5–10cm was achieved using six sensor nodes.
Stress Detection from Speech Using Spectral Slope Measurements
2018
Automatic detection of emotional stress is an active research domain, which has recently drawn increasing attention, mainly in the fields of computer science, linguistics, and medicine. In this study, stress is automatically detected by employing speech-derived features. Related studies utilize features such as overall intensity, MFCCs, Teager Energy Operator, and pitch. The present study proposes a novel set of features based on the spectral tilt of the glottal source and of the speech signal itself. The proposed features rely on the Probability Density Function of the estimated spectral slopes, and consist of the three most probable slopes from the glottal source, as well as the correspon…
On Multiple AER Handshaking Channels Over High-Speed Bit-Serial Bidirectional LVDS Links With Flow-Control and Clock-Correction on Commercial FPGAs f…
2017
Address event representation (AER) is a widely employed asynchronous technique for interchanging “neural spikes” between different hardware elements in neuromorphic systems. Each neuron or cell in a chip or a system is assigned an address (or ID), which is typically communicated through a high-speed digital bus, thus time-multiplexing a high number of neural connections. Conventional AER links use parallel physical wires together with a pair of handshaking signals (request and acknowledge). In this paper, we present a fully serial implementation using bidirectional SATA connectors with a pair of low-voltage differential signaling (LVDS) wires for each direction. The proposed implementation …
Feature selection with Ant Colony Optimization and its applications for pattern recognition in space imagery
2016
This paper presents a feature selection (FS) algorithm using Ant Colony Optimization (ACO). It is inspired by the particular behavior of real ants, namely by the fact that they are capable of finding the shortest path between a food source and the nest. There are considered two ACO-FS model applications for pattern recognition in remote sensing imagery: ACO Band Selection (ACO-BS) and ACO Training Label Purification (ACO-TLP). The ACO-BS reduces dimensionality of an input multispectral image data by selecting the “best” subset of bands to accomplish the classification task. The ACO-TLP selects the most informative training samples from a given set of labeled vectors in order to optimize the…
Change-driven Image Architecture on FPGA with adaptive threshold for Optical-Flow Computation
2006
Optical flow computation has been extensively used for object motion estimation in image sequences. However, the results obtained by most optical flow techniques are as accurate as computationally intensive due to the large amount of data involved. A new strategy for image sequence processing has been developed; pixels of the image sequence that significantly change fire the execution of the operations related to the image processing algorithm. The data reduction achieved with this strategy allows a significant optical flow computation speed-up. Furthermore, FPGAs allow the implementation of a custom data-flow architecture specially suited for this strategy. The foundations of the change-dr…