Motioninsights: real-time object tracking in streaming video

MotionInsights facilitates object detection and tracking from multiple video streams in real-time. Leveraging the distributed stream processing capabilities of Apache Flink and Apache Kafka (as an intermediate message broker), the system models video processing as a data flow stream processing pipeline. Each video frame is split into smaller blocks, which are dispatched to be processed in parallel by a number of Flink operators. In the first stage, each block undergoes background subtraction and component labeling. The connected components from each frame are grouped, and the eligible components are merged into objects. In the last stage of the pipeline, all objects from each frame are concentrated to produce the trajectory of each object. The Flink application is deployed as a Kubernetes cluster in the Google Cloud Platform. Experimenting in a Flink cluster with 7 machines, revealed that MotionInsights achieves up to 6 times speedup compared to a monolithic (nonparallel) implementation while providing accurate trajectory patterns. The highest (i.e., more than 6 times) speed-up was observed with video streams of the highest resolution. Compared to existing systems that use custom or proprietary architectures, MotionInsights is independent of the underlying hardware platform and can be deployed on common CPU architectures and the cloud.