Finding Elbow Angle with Kinect

Finding Elbow Angle with Kinect

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Finding Elbow Angle with Kinect
Tag : chash , By : 40a
Date : November 24 2020, 05:47 AM

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Adjust kinect camera angle using Kinect sdk for windows v 2.0

Tag : chash , By : Don Changer
Date : March 29 2020, 07:55 AM
will be helpful for those in need In the Kinect v2, Microsoft increased the field of view and removed the tilt motor; so it's not possible to adjust the elevation angle anymore. But the good news is that with the expanded field of view, you can see as much as the Kinect 1 without having to move the sensor.
Look at this article, there is a table that clearly shows that Kinect 2 has no tilt motor: http://zugara.com/how-does-the-kinect-2-compare-to-the-kinect-1.

Another function useful than Elbow in finding k-clusters

Tag : machine-learning , By : Tetting
Date : March 29 2020, 07:55 AM
fixed the issue. Will look into that further A metric that you can use to evaluate the result of a clustering is the silhouette coefficient. This value basically computes:
silhouette coefficient = 1 - (intra-cluster cohesion) / (inter-cluster separation)
plot(silhouette(kmeans(df, centers=2)$cluster, dist(df)))
plot(silhouette(kmeans(df, centers=3)$cluster, dist(df)))
plot(silhouette(kmeans(df, centers=4)$cluster, dist(df)))
library(cluster) # for silhouette
library(ggplot2) # for ggplot
library(scales) # for pretty_breaks

# Create sample 2-D data set with clusters around the points (1,1), (2,4), and (3,1)
x<- c(rnorm(n=25, mean=1,sd=.1), rnorm(n=25,mean=2,sd=.1),rnorm(n=25,mean=3,sd=.2))
y<- c(rnorm(n=25, mean=1,sd=.1), rnorm(n=25,mean=4,sd=.1),rnorm(n=25,mean=1,sd=.2))

df <- data.frame(x=x, y=y)

xMax <- max(x)
yMax <- max(y)
print(ggplot(df, aes(x,y)) + geom_point() + xlim(0, max(xMax, yMax)) + ylim(0, max(xMax,yMax)))

# Use the Iris data set.
#df <- subset(iris, select=-c(Species))
#df <- scale(df)

# Run through multiple candidate values of K clusters.

xValues <- c() # Holds the kvalues (x-axis)
yValues <- c() # Holds the silhouette coefficient values (y-axis)
bestKValue <- 0
bestSilhouetteCoefficient <- 0

kSequence <- seq(2, 5)

for (kValue in kSequence) {

    xValues <- append(xValues, kValue)
    kmeansResult <- kmeans(df, centers=kValue, nstart=5)
    silhouetteResult <- silhouette(kmeansResult$cluster, dist(df))
    silhouetteCoefficient <- mean(silhouetteResult[,3])
    yValues <- append(yValues, silhouetteCoefficient)

    if (silhouetteCoefficient > bestSilhouetteCoefficient) {
        bestSilhouetteCoefficient <- silhouetteCoefficient
        bestKValue <- kValue

# Create a dataframe for ggplot to plot the accumulated silhouette values.
dfSilhouette <- data.frame(k=xValues, silhouetteCoefficient=yValues)

# Create the ggplot line plot for silhouette coefficient.
silhouettePlot<- ggplot(data=dfSilhouette, aes(k)) +
    geom_line(aes(y=silhouetteCoefficient)) +
    xlab("k") +
    ylab("Average silhouette width") +
    ggtitle("Average silhouette width") +


printf <- function(...) cat(sprintf(...))
printf("Best Silhouette coefficient=%f occurred at k=%d", bestSilhouetteCoefficient, bestKValue )

How reliable is the Elbow curve in finding K in K-Means?

Tag : python , By : Shane
Date : March 29 2020, 07:55 AM
wish helps you The "Elbow" is not even well defined. So how can it be reliable?
You can "normalize" the values by the expected dropoff from splitting the data into k clusters and it will become a bit more readable. Unfortunately, I forgot the exact name of that.Calinski and Harabasz (1974) variance ratio criterion? If I recall the name correctly, that is essentially a rescaled version that makes much more sense.

Representing robot's elbow angle in 3-D

Tag : development , By : Boyer C.
Date : March 29 2020, 07:55 AM

Finding the elbow/knee in a curve

Tag : r , By : baylisscg
Date : March 29 2020, 07:55 AM
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