Stocks that are fundamentally connected with each other tend to move together. Considering
such common trends is believed to benefit stock movement forecasting tasks. However, such …

As one of the most important affective signals, facial affect analysis (FAA) is essential for
developing human-computer interaction systems. Early methods focus on extracting …

This paper presents a new face descriptor, local directional ternary pattern (LDTP), for facial
expression recognition. LDTP efficiently encodes information of emotion-related features (ı …

In this paper, a local spatiotemporal descriptor, namely, the volume local binary count
(VLBC), is proposed for the representation and recognition of dynamic texture. This …

Anomaly detection suffers from unbalanced data since anomalies are quite rare.
Synthetically generated anomalies are a solution to such ill or not fully defined data …

Abstract Dynamic Textures (DTs) are sequences of images of moving scenes that exhibit
certain stationarity properties in time such as smoke, vegetation and fire. The analysis of DT …

Many researchers focus on the local feature-based description of the dynamic texture,
because of its stability and low dimensionality. Among the existing dynamic texture …

Representing dynamic textures (DTs) plays an important role in many real implementations
in the computer vision community. Due to the turbulent and non-directional motions of DTs …

In this paper, a new dynamic facial expression recognition method is proposed. Dynamic
facial expression recognition is formulated as a longitudinal groupwise registration problem …

State-of-the-art image-set matching techniques typically implicitly model each image-set with
a Gaussian distribution. Here, we propose to go beyond these representations and model …