Innovative algorithm of the object detection in videos at the ISM 2019
Hannes Fassold, senior researcher at JOANNEUM RESEARCH - DIGITAL, gave a talk at the IEEE ISM conference about resource-efficient object detection by sharing backbone CNNs. This work (jointly done with Werner Bailer) addresses the problem of sharing a backbone CNN for different tasks, for example, to enable detection of additional classes when an already trained network is available. Furthermore, he presented a poster about realtime detection and tracking of objects, text and logos in conventional as well as 360° video. It combines a powerful Deep Learning based object detector (YoloV3) with high-quality optical flow methods.
Both works are very important for many application cases (like realtime video processing, autonomous drivng and edge computing), where it is crucial to have a lightweight network which can operate in realtime on the device.
Research in multimedia computing is generally concerned with presentation, integration and computation of one or more media, such as text, image, graphics, audio, video, social data, and data collected from various sensors, etc., using computing techniques. The 21st IEEE International Symposium on Multimedia (ISM 2019) took place in San Diego in December 2019. It is the flagship conference of IEEE Technical Committee on Multimedia (TCMC) and an international forum for researchers to exchange information regarding advances in the state of the art and practice of multimedia computing, as well as to identify the emerging research topics and to define the future of multimedia computing.