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Course Detail

Course Name Video Analytics
Course Code 18CS711
Credits Coimbatore
Year Taught 2018


Course Syllabus

Computational Statistics- Probability concepts, Sampling Concepts, Generating Random Variables, Exploratory Data Analysis, Monte Carlo Methods for Inferential Statistics, Data Partitioning, Probability Density Estimation, Statistical Pattern Recognition, Nonparametric Regression. Data Mining- data mining algorithms-Instance and Features, Types of Features (data), Concept Learning and Concept Description, Output of data mining Knowledge Representation; Decision Trees- Classification and Regression trees constructing.

Classification trees, Algorithm for Normal Attributes, Information Theory and Information. Entropy, Building tree, Highly-Branching Attributes, ID3 to c4.5, CHAID, CART, Regression Trees, Model Trees, Pruning. Preprocessing and Post processing in data mining – Steps in Preprocessing, Discretization, Manual Approach, Binning, Entropy- based Discretization, Gaussian Approximation, K-tile method, Chi Merge, Feature extraction, selection and construction, Feature extraction, Algorithms, Feature selection, Feature construction, Missing Data, Post processing. Association Rule Mining- The Apriori Algorithm. Multiple Regression Analysis, Logistic Regression, k- Nearest Neighbor Classification, Constructing new attributes for algorithms of decision trees. Induction, Quick, Unbiased and Efficient Statistical tree.

Course Outcome

Evaluation Pattern

  • Periodical 1 – 15
  • Periodical 2 – 15
  • Continuous Evaluation – 20
  • End Semester – 50

At the end of the course the students will be able to

Course Outcome Bloom’s Taxonomy Level
CO 1 Understand the algorithms available for performing analysis on video data and address the challenges L2
CO 2 Understand the approaches for identifying and tracking objects and person with motion based algorithms. L2
CO 3 Understand the algorithms available for searching and matching in video content L2
CO 4 Analyze approaches for action representation and recognition L4
CO 5 Identify, Analyze and apply algorithms for developing solutions for real world problems L6

Text Books / References

  1. Richard Szeliski, “Computer Vision: Algorithms and Applications”, Springer, 2011.
  2. Yao Wang, JornOstermann and Ya-Qin Zhang, “Video Processing and Communications”, Prentice Hall, 2001.
  3. A.MuratTekalp, “Digital Video Processing”, Pearson, 1995
  4. Thierry Bouwmans, FatihPorikli, Benjamin Höferlin and Antoine Vacavant, “Background Modeling and Foreground Detection for Video Surveillance: Traditional and Recent Approaches, Implementations, Benchmarking and Evaluation”, CRC Press, Taylor and Francis Group, 2014.
  5. Md. Atiqur Rahman Ahad, “Computer Vision and Action Recognition-A Guide for Image Processing and Computer Vision Community for Action Understanding”, Atlantis Press, 2011.


‘Video Analytics’ is an elective course offered in M. Tech. in Computer Science and Engineering program at School of Engineering, Amrita Vishwa Vidyapeetham.

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