Search results for "Context"
showing 10 items of 6304 documents
Towards a Hierarchical Multitask Classification Framework for Cultural Heritage
2018
Digital technologies such as 3D imaging, data analytics and computer vision opened the door to a large set of applications in cultural heritage. Digital acquisition of a cultural assets takes nowadays a couple of seconds thanks to the achievements in 2D and 3D acquisition technologies. However, enriching these cultural assets with labels and relevant metadata is still not fully automatized especially due to their nature and specificities. With the recent publication of several cultural heritage datasets, many researchers are tackling the challenge of effectively classifying and annotating digital heritage. The challenges that are often addressed are related to visual recognition and image c…
«Motion Estimation Accelerator with User Search Strategy in an RVC Context»
2009
Motion estimation represents a key module in video compression. The RVC context requires proposing a flexible solution for motion estimation. According to the nature of the application, a full search is sometimes not suitable, hence, alternative fast/reduced solutions should be considered. This paper proposes a model and implementation of a flexible motion estimation engine, which can be configured to support any user-defined search strategy. Typically, the computational requirements of the search strategy can be traded with the RD-performance of the obtained video encoder. A CAL dataflow description of the accelerator is proposed so that it can be easily handled in the RVC context. An auto…
Experiencing with electronic image stabilization and PRNU through scene content image registration
2021
Abstract This paper explores content-based image registration as a means of dealing with and understanding better Electronic Image Stabilization (EIS) in the context of Photo Response Non-Uniformity (PRNU) alignment. A novel and robust solution to extrapolate the transformation relating the different image output formats for a given device model is proposed. This general approach can be adapted to specifically extract the scale factor (and, when appropriate, the translation) so as to align native resolution images to video frames, with or without EIS on, and proceed to compare PRNU patterns. Comparative evaluations show that the proposed approach outperforms those based on brute-force and p…
Lists of Spanish sentences with equivalent predictability, phonetic content, length, and frequency of the last word.
2010
This paper presents a pool of Spanish sentences designed for use in cognitive research and speech processing in circumstances in which the effects of context are relevant. These lists of sentences are divided into six lists of 25 equivalent high-predictability sentences and six lists of 25 low-predictability sentences according to the extent to which the last word can be predicted by the preceding context. These lists were also equivalent in phonetic content, length and frequency of the last word. These lists are intended for use in psycholinguistic research with Spanish-speaking listeners.
Area-Based Depth Estimation for Monochromatic Feature-Sparse Orthographic Capture
2018
With the rapid development of light field technology, depth estimation has been highlighted as one of the critical problems in the field, and a number of approaches have been proposed to extract the depth of the scene. However, depth estimation by stereo matching becomes difficult and unreliable when the captured images lack both color and feature information. In this paper, we propose a scheme that extracts robust depth from monochromatic, feature-sparse scenes recorded in orthographic sub-aperture images. Unlike approaches which rely on the rich color and texture information across the sub-aperture views, our approach is based on depth from focus techniques. First, we superimpose shifted …
Kernel-Based Framework for Multitemporal and Multisource Remote Sensing Data Classification and Change Detection
2008
The multitemporal classification of remote sensing images is a challenging problem, in which the efficient combination of different sources of information (e.g., temporal, contextual, or multisensor) can improve the results. In this paper, we present a general framework based on kernel methods for the integration of heterogeneous sources of information. Using the theoretical principles in this framework, three main contributions are presented. First, a novel family of kernel-based methods for multitemporal classification of remote sensing images is presented. The second contribution is the development of nonlinear kernel classifiers for the well-known difference and ratioing change detectio…
On Contextuality in Behavioral Data
2015
Dzhafarov, Zhang, and Kujala (Phil. Trans. Roy. Soc. A 374, 20150099) reviewed several behavioral data sets imitating the formal design of the quantum-mechanical contextuality experiments. The conclusion was that none of these data sets exhibited contextuality if understood in the generalized sense proposed in Dzhafarov, Kujala, and Larsson (Found. Phys. 7, 762-782, 2015), while the traditional definition of contextuality does not apply to these data because they violate the condition of consistent connectedness (also known as marginal selectivity, no-signaling condition, no-disturbance principle, etc.). In this paper we clarify the relationship between (in)consistent connectedness and (non…
Multi-agent Reinforcement Learning for Simulating Pedestrian Navigation
2012
In this paper we introduce a Multi-agent system that uses Reinforcement Learning (RL) techniques to learn local navigational behaviors to simulate virtual pedestrian groups. The aim of the paper is to study empirically the validity of RL to learn agent-based navigation controllers and their transfer capabilities when they are used in simulation environments with a higher number of agents than in the learned scenario. Two RL algorithms which use Vector Quantization (VQ) as the generalization method for the space state are presented. Both strategies are focused on obtaining a good vector quantizier that generalizes adequately the state space of the agents. We empirically state the convergence…
Dynamics-based action recognition for motor intention prediction
2020
Abstract Powered lower-limb prostheses presented in the previous chapter require a natural and easy-to-use interface for communicating amputee’s motor intention in order to select the appropriate motor program in a given context or simply to commute from an active (powered) to a passive mode of functioning. To be accepted by amputees, such an interface should (1) not put additional cognitive load on the end-user, (2) be reliable and (3) be minimally invasive. In this chapter we present one possible solution for achieving that goal: a robust method for autonomously detecting and recognizing motor intents from a wearable sensor network mounted on a sound leg. The sensor network provides a rea…
Comparing Tangible and Fully Virtual Haptic Systems for HMI Studies in Simulated Driving Situations
2019
International audience; The contribution of tangible and intangible feedback is compared for virtual tactile car Human-Machine Interfaces (HMI) design, to measure their performance both in static conditions and while driving. A subjectively calibrated transparent glass provides tangible passive haptics, and visual cues are used to study sensory substitution-based intangible interactions. The results show that the performance of the subjects was significantly improved in driving conditions as they interacted faster, more accurately and with a higher satisfaction. In addition, our findings highlight that the contribution of tangible systems is significantly lower in driving conditions, raisin…