Video streaming using Apache Kafka and OpenCV libraries. The motivation behind the project is the need for effective management and analysis of large-scale video streams generated from sources such as surveillance cameras. Kafka is a distributed message streaming platform that is resilient to node failure and supports automatic recovery. OpenCV is an open-source image processing library designed for real-time applications, including the processing and analysis of images and videos. The project uses Kafka for real-time data acquisition, OpenCV for video rendering, and Flask for the distributed consumer. The video client generates data as a producer, which streams video directly from a webcam in real-time and converts it into a stream of JPEG images.
- Pandey, A., & Singh, H. 2018. Face Recognition of Pedestrians from Live Video Stream using Apache Spark Streaming and Kafka. International Journal of Innovative Technology and Exploring Engineering (IJITEE). Vol. 7
- Chen, H., Luo, F., Zhao, L & Li, Y. 2017. Design and Implementation of Real-Time Video Big Data Platform based on Spark Streaming. 2017 International Conference on Computer Science and Application Engineering (CSAE 2017)
- Kreps, J., Narkhede, N., & Rao, J. 2011. Kafka: A Distributed Messaging System for Log Processing
- Bradski, G. and Kaehler, A., 2008. Learning OpenCV: Computer vision with the OpenCV library. " O'Reilly Media, Inc.".