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Multi-modal fusion for video understanding
Proceedings 30th Applied Imagery Pattern Recognition Workshop (AIPR 2001). Analysis and Understanding of Time Varying Imagery, 2002The exploitation of semantic information in computer vision problems can be difficult because of the large difference in representations and levels of knowledge. Image analysis is formulated in terms of low-level features describing image structure and intensity, while high-level knowledge such as purpose and common sense are encoded in abstract, non ...
Anthony Hoogs +2 more
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On Multi-modal Fusion Learning in constraint propagation
Information Sciences, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yaoyi Li, Hongtao Lu 0001
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Commuting Conditional GANS for Multi-Modal Fusion
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020This paper presents a data driven approach to multi-modal fusion where a hidden latent sub-space between the different modalities is learned. The hidden space is estimated via a bank of Conditional GANs which also commute with each other, leading to an output that lies in a common subspace.
Siddharth Roheda +2 more
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Multi-modal Fusion for Video Sentiment Analysis
Proceedings of the 1st International on Multimodal Sentiment Analysis in Real-life Media Challenge and Workshop, 2020Automatic sentiment analysis can support revealing a subject's emotional state and opinion tendency toward an entity. In this paper, we present our solutions for the MuSe-Wild sub-challenge of Multimodal Sentiment Analysis in Real-life Media (MuSe) 2020. The videos in this challenge are collected from YouTube about emotional car reviews.
Ruichen Li +4 more
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Multi-modal identity verification using expert fusion
Information Fusion, 2000 The contribution of this paper is to compare paradigms coming from the classes of parametric, and non-parametric techniques to solve the decision fusion problem encountered in the design of a multi-modal biometrical identity verification system.
Gérard Chollet
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Tracking Humans using Multi-modal Fusion
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops, 2006Human motion detection plays an important role in automated surveillance systems. However, it is challenging to detect non-rigid moving objects (e.g. human) robustly in a cluttered environment. In this paper, we compare two approaches for detecting walking humans using multi-modal measurements- video and audio sequences.
Xiaotao Zou, Bir Bhanu
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Multi-modal decision fusion for continuous authentication
Computers & Electrical Engineering, 2015Display Omitted Behavioral biometrics: keystroke dynamics, mouse movement, stylometry.A parallel binary decision fusion architecture with 11 sensors.A dataset collected from 67 users each working in an office environment for a week.Achieve below 1% error rates (FAR, FRR) after only 30s of activity.Characterize robustness of system to adversarial ...
Lex Fridman 0001 +6 more
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On Multi-modal Fusion for Freehand Gesture Recognition
2020We present a study of multi-modal freehand gesture recognition relying on three sensory modalities. The modalities are RGB images, depth data, and acceleration data from an IMD attached to the hand. Based on a new self-recorded dataset, we initially establish the ability of a deep Long Short-Term Memory (LSTM) network to correctly classify individual ...
Monika Schak, Alexander Gepperth
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Multi-modal Data Fusion: A Description
2004Clustering groups records that are similar to each other into the same group, and those that are less similar into different groups. Clustering data of mixed types is difficult due to different data characteristics. Extending Gower’s metric for nominal and ordinal data is incorporated into an agglomerative hierarchical clustering algorithm to cluster ...
Sarah Coppock, Lawrence J. Mazlack
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The one-to-many multi-modal fusion challenge
2012 5th IAPR International Conference on Biometrics (ICB), 2012The One-to-many Multi-modal Fusion Challenge is presented, with the aim of promoting academic research into one-to-many methods of fusion for large-scale biometric systems. Although most research into fusion has been conducted using verification (one-to-one) comparison results, there is greater demand among government agencies for one-to-many fusion ...
George W. Quinn, Patrick Grother
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