1 research outputs found
OmniTrack: Real-time detection and tracking of objects, text and logos in video
The automatic detection and tracking of general objects (like persons,
animals or cars), text and logos in a video is crucial for many video
understanding tasks, and usually real-time processing as required. We propose
OmniTrack, an efficient and robust algorithm which is able to automatically
detect and track objects, text as well as brand logos in real-time. It combines
a powerful deep learning based object detector (YoloV3) with high-quality
optical flow methods. Based on the reference YoloV3 C++ implementation, we did
some important performance optimizations which will be described. The major
steps in the training procedure for the combined detector for text and logo
will be presented. We will describe then the OmniTrack algorithm, consisting of
the phases preprocessing, feature calculation, prediction, matching and update.
Several performance optimizations have been implemented there as well, like
doing the object detection and optical flow calculation asynchronously.
Experiments show that the proposed algorithm runs in real-time for standard
definition () video on a PC with a Quadro RTX 5000 GPU.Comment: accepted for IEEE ISM Conference, 201