Computer vision is applied in many software and devices. The detection and
reconstruction of the human skeletal structure is one of area of interest, where the
camera will identify the human parts and construct the joints of the person standing in
front. Three-dimensional pose estimation is solved using various learning approaches,
such as Support Vector Machines and Gaussian processes. However, difficulties in
cluttered scenarios are encountered, and require additional input data, such as
silhouettes, or controlled camera settings. The paper focused on estimating the threedimensional
pose of a person without requiring background information, which is
robust to camera variations. Each of the joint has three-dimensional space position and
matrix orientation with respect to the sensor. Matlab Simulink was utilized to provide
communication tools with depth camera using Kinect device for skeletal detection.
Results on the skeletal detection using Kinect sensor is analysed in measuring the
abilities to detect skeletal structure accurately, and it is shown that the system is able
to detect human skeletal performing non-complex basic motions in daily life.
A comparative analysis of metabolites from different parts of Curcuma aeruginosa, i.e. leaves, stems, adventitious
roots and rhizomes was performed by GC-MS/MS coupled with multivariate statistical analysis. The GC-MS/MS analysis
confirmed the occurrence of 26 metabolites belonged to terpenoids in almost all the samples. The Principal Component
Analysis (PCA) indicated that there was a clear distinction between rhizomes and other plant parts, i.e. stems, leaves,
and adventitious roots that could be explained by relatively higher contents of terpenoids including curzerene, alphafarnesen, furanocoumarin, velleral, germacrone cineole, borneol, beta- and gamma- elemene and methenolone. The
results of Hierarchical Clustering Analyses (HCA) corresponded with the PCA results where many terpenoids found
abundantly high in rhizome were clustered together. This was supported by the Pearson correlation analysis that
showed a significantly good relationship between those terpenoids. The adventitious roots demonstrated the strongest
antioxidant activity as compared to the other plant parts which could be attributed to its highest Total Phenolic
Contents (TPC). Total phenolic contents of all the plant parts were positively correlated with their antioxidant activities
which indicate that phenolic compounds may play a role in the overall antioxidant activities of the plants. The results
of the study highlighted the potential of this underexploited Curcuma species which could serve as a new source of
important phytochemicals and natural antioxidant that could be incorporated in functional foods and nutraceuticals.
In addition, chemical and biological evidence shown in the present work has rationalised the different uses of various
plant parts of C. aeruginosa.