Availability of humungous visual data and increasing in generation of visual data in Security and Surveillance domain made a pathway to Computer Vision algorithms. The existing algorithms are not precise enough for predictive analytics. Sensitive use cases such as action recognition and identifying missing people in huge crowds has thrown a challenging research of drawing accurate and precise results. The existing 2-D plots for action recognition have failed due to unstructured visual data available where the accuracy is around <50%. Due to unstructured visual data, the existing 3-D plots often get overlapped with each other. Although the accuracy is noted >90% which maps it to False Positives. The existing solutions deals with object detection through Boolean logic then Pose Plots are mapped. Our research focus in on reverse engineer the existing solutions by applying smart segmentation to isolate background and then map the pose formula to detect the action. Our proposed solution obliterates the over-lap complications and unravels the False Positives. Our proposed solution achieved accuracy and precision of mAP>0.8 for both images and video feeds.
Tracking of ball in sports videos is one of the most challenging tasks in computer vision and video processing domain. Recent ball tracking approaches fail to handle tracking of a small size and fast moving ball. Inaccurate 2D ball detection leads to further deterioration of 3D ball tracking results. This paper presents a soccer ball tracking by detection approach using a pre-trained Convolutional Neural Network (CNN). The proposed algorithm used CNN for identifying ball from background and other moving objects like players and referees. The 2D ball detection results are fine-tuned for identifying true ball positions. True ball positions, from cameras shooting the scene from different angle, are further mapped on ground plane. The actual ball movement is tracked in 3D from top-view. Experiments show that the proposed algorithm can tackle challenges like small ball size, shape changes, occlusion and tracking high-speed balls.