Spatial-Temporal Model for Emotion Interpretation

Spatial-Temporal Model for Emotion Interpretation

Interpreting facial expressions is a task that humans perform everyday automatically. Most of gesture recognition research are focused to discriminate different facial expressions, while interpreting them is relatively a new area. This paper deals with how to recognize an emotional state, since it can be represented as states at a time t that are influenced directly by a previous state at t − 1...

Spatial-temporal modeling of interactive image interpretation.

We consider the problem of spatial-temporal modeling of interactive image interpretation. The interactive process is composed of a sequential prediction step and a change detection step. Combining the two steps leads to a semi-automatic predictor that can be applied to a time-series, yields good predictions, and requests new human input when a change point is detected. The model can effectively...

Spatial-Temporal Junction Extraction and Semantic Interpretation

This article describes a novel junction descriptor that encodes junctions’ semantic information in terms incoming lines’ orientations, both in 2D and 3D. A Kalman filter process is used to reduce the effect of local noise on the descriptor’s error and to track the features. The improvement gained by our algorithm is demonstrated quantitatively on synthetic scenes and qualitatively on real scenes.

Spatial-Temporal Recurrent Neural Network for Emotion Recognition

Emotion analysis is a crucial problem to endow artifact machines with real intelligence in many large potential applications. As external appearances of human emotions, electroencephalogram (EEG) signals and video face signals are widely used to track and analyze human’s affective information. According to their common characteristics of spatial-temporal volumes, in this paper we propose a nove...

Planning for Protected Areas Using Spatial and Temporal Metrics