LAB 3 Report - SAISRIHARSHAS/Big-Data-Analytics-and-Applications-CS5542 GitHub Wiki

Question: A group of primatologists wants to study the details of the daily movement, activities, and interactions of a group of 6 chimpanzees living on "chimp island" - a natural,though somewhat open habitat about 50 meters in diameter, bounded on all sides by water, in the San-Diego zoo. Since they don't want to sit all day every day recording the second-by second positions and activities of the chimps, they have come to you, a computer vision expert, for automated assistance. They are interested in both compiling statistics about the movement and location of individuals, and in the frequency and locations of different interactions and activities (feeding, sleeping, grooming, fighting, etc.) They are willing to help in labeling relevant activities, even to the point of answering a few hundred quick questions per day of data (what's she doing here?), but they don't want to sit through 24 hours of video to do it. Ultimately they want an automated database that they can use to find out how many hours a day chimp Jane sleeps and where,histogram preferred eating locations, obtain statistics on who grooms whom, etc.

Implement to build a linear regression model for selected two parameters for chimpanzee’s daily movement, activities and interaction. Define your own data sets.

Implement K-Means clustering for the clusters of the chimpanzee’s activities. Define your own data sets.

Answer: Linear Regression

For Linear Regression model, I took all the chimpanzees and recorded their activities like feeding, sleeping, grooming, fighting etc. in periodic(daily) succession. Based on the reading, I have chosen the Input data set to represent the values to the 2 decimal places for better readability.

After the compilation and execution of the program, I got

training Mean Squared Error = 0.685036161263114

test Mean Squared Error = 0.25765408263051437

From the above two results, it is shown that the values are accurate with the real-world data as there is minimal value difference between the training(95%) and test data(5%)

local host:

USED THE MP4 FILE PROVIDED IN THE LAB TUTORIAL.

Screenshots: INPUT

output:

kMeans Clustering

For kMeans clustering, I have taken two axis (X and Y axis)

X-axis: Location of Chimpanzees

Y-axis: Activities (feeding,fighting, grooming, sleeping etc)

After plotting the graph (imaginary), we can start clustering the data points. Since I gave 3 clusters. The values are grouped equally in each of the three clusters. Finally, the

Within Set Sum of Squared Errors = 0.8199500000000315

is minimal which suggests that the values are accurate

Screenshots: K-MEANS INPUT

K-MEANS OUTPUT:

PROBLEM: Build a simple application to give the summary of a video by using Clarifai API. Using OpenImg Library to the key-frame images from the clarifai API. IMPLEMENTATION: Step-1: Key Frame Detection Using OpenIMAJ CODE: EXECUTION:

FRAMES AND MAINFRAMES

Step-2: Annotation for each Key Frame image CODE:

OUTPUT:

Step-3: Creating Summary of the Video

Extracted top 5 objects in each MainFrame based on the values associated with them. Stored these objects in a 2-Dimensional Array for further processing. Created a summary based on the values in the array (annotations), MainFrame and the Video.

Parsing the Image Annotation Content into a 2-Dimensional Array

output Summary: