Mini-Project #3: Forward/Inverse Kinematics (Due by 11/25/11)In this assigment, you need to implement forward kinematics and Inverse kinematics algorithms for a full-body human character. The skeletal model of your character is described by .asf file. You should choose an appropriate geometric primitive (e.g. ellipsoid) to visualize each bone.1. Forward kinematics (40 points):1.1 Read .asf and .amc file. The details of both files are discussed described in our class. (10 points)1.2 demonstrate the performance of your FK algorithm with the following applications:- visualize a sequence of human body poses from input mocap data files (.amc and .asf). (10 points)- pick a point p on the character, compute and visualize its 3D trajectory across the entire sequence. (10 points)- pick a frame in the .amc file, compute 3D positions of all joints. (10 points)2. Inverse kinematics with nonlinear optimization (60 points):- First, you need to demonstrate how to apply inverse kinematics techniques to compute 3D joint angle values based on 3D positions of all joints obtained in step 1.2. Note that you can evaluate the effectiveness of your system by comparing the computed posed against ground truth values. (50 points) - Second, you need to extend your IK system to pose a human character with direct manipulation interfaces. More specifically, the system allows the user to pick any points on the character and interactively manipulate the character pose by continuously dragging the point in 2D screen space. (10 points)3. (Bonus points). You can earn extra points by doing the following tasks:- adding joint angle limits to your IK algorithm (bonus points: 10)- use analytical jacobian matrix for IK process (bonus points: 20)- retargeting source motions from one character to another one. Note that you can create a new character by modifying bone skeletal lengths of .skeleton files (.ASF). (bonus points: 20).4. Startup code structure, optimization library, and motion capture data4.1 To help you finish your homework, we provide you skeleton code: http://faculty.cs.tamu.edu/jchai/csce641/asf_amc_viewer.zipThe program uses OpenGL library to visualize motion capture data (.asf and .amc files). It also uses the FLTK library (http://www.fltk.org/ ) for interface programming. The sample test motion files are put in the “Test Data” sub directory. You can download more mocap data files from the CMU online mocap database: http://mocap.cs.cmu.edu/motcat.php The “instruction.txt” shows you how to compile the code with Microsoft visual studio. The Class “Explain.doc” shows an overview of every C++ class. To know more details of the code, read the comments in the code.Note that you can also download C++ startup codes from http://mocap.cs.cmu.edu/tools.php.4.2 I encourage you to use Levenberg-Marquardt nonlinear least squares algorithms to implement IK. Here (http://www.ics.forth.gr/~lourakis/levmar/) is the website to download the optimization library. 4.3 For experiments, you can either download testing motion capture data files from an online cmu mocap library (http://mocap.cs.cmu.edu) or capture your own data from mocap lab located in HRBB 505. Contact me early if you want to capture your own