Spatiotemporal optical blob reconstruction for object detection in grayscale videos

摘要

There has been a significant research devoted towards detection of a moving object in an image sequence. Detected moving objects usually contain some errors (some pixels belonging to the object are marked as non-objects and vice versa). To achieve a refined detection of moving object in the video, there is a need of post processing of the binary blobs detected as objects in every frame of the video. This article introduces a novel blob reconstruction method that overcomes the mentioned limitation through optical flow based nullification, bifurcation, and unification of detected blobs. To claim the performance of the proposed method, a comparison is made with ten widely used object detection methods on twenty four standard moving-object scene videos. Comparison is made based on standard parameters like accuracy, precision, recall, and F-measure. The results clearly indicates the efficacy of the proposed method. Following this, results on a priliminary case study on placodal cell migration during early development of ectodermal organ of human and mice has been made employing the proposed model which promisingly tracks the cell migration.