Your English writing platform
Discover LudwigExact(13)
Figure 17 Scatter diagram of the trajectory feature space.
A slight bias in the third principal component was confirmed in the trajectory feature space.
Thus, it is hard to distinguish the trajectory from other normal trajectories in the trajectory feature space.
We could confirm a large bias on the axis of the first principal component in the trajectory feature space.
Researchers have proposed several features to extract different information of videos, such as the dense trajectory feature, STIP, SIFT, and so on.
Figure 17 shows a scatter diagram of trajectories in the trajectory feature space of the axis of primary components one to three.
Similar(47)
We employ the dense trajectory features.
Second, abnormal events are successfully detected by combining the Random Forest classifier and the trajectory features.
We first extract dense trajectory features from videos, and then MBH and HOF descriptors are computed along each trajectory.
By integrating interactive visual exploration and statistical analysis of trajectory features, our workflow supports both qualitative and quantitative analyses.
As Fig. 1 shows, we extract dense trajectory features from the videos and encode each feature to three different descriptors which are HOG, HOF, and MBH.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com