Thermal Signature Using Non-redundant Temporal Local Binary-Based Features

International audienceIn this paper, we propose a method for event recognition from thermal signature based 1-D signal. We use the non-redundant temporal Local Binary Pattern NRTLBP as a descriptor of the Pattern Of Interest (POI) signal. The original signal is extracted directly from local patch in region of interest. We introduce the wavelet decomposition as a pre-processing stage in order to extract the approximation wave-components of the raw signal. Then, NRTLBP is applied on the wave-components which provide wavelet domain descriptor of the raw thermal signature. Finally, we provide an evaluation of our method on the real dataset (Preterm Pain in Infants “PPI” ) composed of thermal videos developed in the context of Infant pain project, a french project supported by the French National Research Agency Projects for science (ANR)

Thermal Signature Using Non-redundant Temporal Local Binary-Based Features

International audienceIn this paper, we propose a method for event recognition from thermal signature based 1-D signal. We use the non-redundant temporal Local Binary Pattern NRTLBP as a descriptor of the Pattern Of Interest (POI) signal. The original signal is extracted directly from local patch in region of interest. We introduce the wavelet decomposition as a pre-processing stage in order to extract the approximation wave-components of the raw signal. Then, NRTLBP is applied on the wave-components which provide wavelet domain descriptor of the raw thermal signature. Finally, we provide an evaluation of our method on the real dataset (Preterm Pain in Infants “PPI” ) composed of thermal videos developed in the context of Infant pain project, a french project supported by the French National Research Agency Projects for science (ANR)