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Background segmentation with feedback: The Pixel-Based Adaptive Segmenter
TLDR
In this paper, a novel method for foreground segmentation is presented that follows a non-parametric background modeling paradigm, thus the background is modeled by a history of recently observed pixel values and the background update is based on a learning parameter.
SVC2004: First International Signature Verification Competition
TLDR
The First International Signature Verification Competition (SVC2004) recently was organized as a step towards establishing common benchmark databases and benchmarking rules and the experience gained will be very useful to similar activities in the future.
Cross-Corpus Acoustic Emotion Recognition: Variances and Strategies
TLDR
Results employing six standard databases in a cross-corpora evaluation experiment show the crucial performance inferiority of inter to intracorpus testing and investigates different types of normalization.
Speech emotion recognition combining acoustic features and linguistic information in a hybrid support vector machine-belief network architecture
TLDR
A novel approach to the combination of acoustic features and language information for a most robust automatic recognition of a speaker's emotion by applying belief network based spotting for emotional key-phrases is introduced.
Acoustic emotion recognition: A benchmark comparison of performances
TLDR
The largest-to-date benchmark comparison under equal conditions on nine standard corpora in the field using the two pre-dominant paradigms is provided, finding large differences are found among corpora that mostly stem from naturalistic emotions and spontaneous speech vs. more prototypical events.
Hidden Markov model-based speech emotion recognition
TLDR
The paper addresses the design of working recognition engines and results achieved with respect to the alluded alternatives and describes a speech corpus consisting of acted and spontaneous emotion samples in German and English language.
Hypergraphs for Joint Multi-view Reconstruction and Multi-object Tracking
TLDR
This work presents a combined maximum a posteriori (MAP) formulation, which jointly models multicamera reconstruction as well as global temporal data association, and a flow graph is constructed, which tracks objects in 3D world space.
2.5D gait biometrics using the Depth Gradient Histogram Energy Image
TLDR
The traditional Gait Energy Image is extended by including depth information, and a completely new feature is formed, which is called the Depth Gradient Histogram Energy Image (DGHEI).
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