Abstract: The paper proposes a way of parallel processing of
SURF and Optical Flow for moving object recognition and tracking.
The object recognition and tracking is one of the most important task
in computer vision, however disadvantage are many operations cause
processing speed slower so that it can-t do real-time object recognition
and tracking. The proposed method uses a typical way of feature
extraction SURF and moving object Optical Flow for reduce
disadvantage and real-time moving object recognition and tracking,
and parallel processing techniques for speed improvement. First
analyse that an image from DB and acquired through the camera using
SURF for compared to the same object recognition then set ROI
(Region of Interest) for tracking movement of feature points using
Optical Flow. Secondly, using Multi-Thread is for improved
processing speed and recognition by parallel processing. Finally,
performance is evaluated and verified efficiency of algorithm
throughout the experiment.
Abstract: In this study we tried to replicate the unconscious
thought advantage (UTA), which states that complex decisions are
better handled by unconscious thinking. We designed an experiment
in e-prime using similar material as the original study (choosing
between four different apartments, each described by 12 attributes).
A total of 73 participants (52 women (71.2%); 18 to 62 age:
M=24.63; SD=8.7) took part in the experiment. We did not replicate
the results suggested by UTT. However, from the present study we
cannot conclude whether this was the case of flaws in the theory or
flaws in our experiment and we discuss several ways in which the
issue of UTA could be examined further.