Open AccessMoving Object Detection and Tracking under Different Occlusion Conditions in Video Sequences
Author(s) -
Arjun Nelikanti,
G. Karuna,
G. Venkata Rami Reddy
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.k1951.0981119
Subject(s) - computer vision , artificial intelligence , video tracking , computer science , object (grammar) , tracking (education) , occlusion , kalman filter , object detection , window (computing) , set (abstract data type) , pattern recognition (psychology) , medicine , psychology , pedagogy , cardiology , programming language , operating system
This paper proposed a novel method for the detection and tracking of hand-thrown object in a video sequence in real time sports events. This paper mainly aimed to detect regions of the object in a set of outdoor and indoor videos in different occlusion conditions, and used Kalman filter to detect object on different trajectories over a fixed time window. This approach proved that the thrown object is successfully detected in various cases under occlusion and non-occlusion conditions with different backgrounds. To evaluate the accuracy, two different types of performance evaluations metrics are used based on object detection and tracking. The results shows that significant performance, the average accuracy of the object detecting is 97.89% and tracking is 98.35%