International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 163 - Number 4 |
Year of Publication: 2017 |
Authors: R. Kousalya, S. Dharani |
10.5120/ijca2017913495 |
R. Kousalya, S. Dharani . Multiple Video Instance Detection and Retrieval using Spatio-Temporal Analysis using Semi Supervised SVM Algorithm. International Journal of Computer Applications. 163, 4 ( Apr 2017), 12-19. DOI=10.5120/ijca2017913495
Object instance search aims to not solely retrieve the pictures or frames that contain the query, however additionally find all its occurrences. During this work, we tend to explore the utilization of spatio-temporal cues to enhance the standard of object instance search from videos. To the present finish, the work to formulate this drawback because the spatio-temporal trajectory search downside, wherever a trajectory may be a sequence of bounding boxes that find the thing instance in every frame. The goal is to seek out the top- trajectories that are possible to contain the target object. The work tends to solve the key bottleneck in applying the approach to object instance search by leverage a randomized approach to change quick marking of any bounding boxes within the video volume.