Cricket shot classification using motion vector

Cricket shots cannot be detected yet from single video sample without multiple view camera and other tools like sonar, speedometer. Extracting salient feature and optical flow from videos of cricket shots is still a challenge. In cricket, body parts movement created several different directional optical flows. So we propose motion estimation approach related to classifying the shots using 3D MACH for action recognition. Our methodology defines 8 classes of angle ranges to detect cricket shots. Our method is grounded on Motion vectors that help to measure the angle of any precise cricket shot. An adequate accuracy level for the shots is established for this particular approach.