Objects Talk - Object Detection and Pattern Tracking Using TensorFlow

Objects in household that are frequently in use often follow certain patterns with respect to time and geographical movement. Analysing these patterns can help us keep better track of our objects and maximise efficiency by minimizing time wasted in forgetting or searching for them. In our project, we used TensorFlow, a relatively new library from Google, to model our neural network. The TensorFlow Object Detection API is used to detect multiple objects in real-time video streams. We then introduce an algorithm to detect patterns and alert the user if an anomaly is found. We consider the research presented by Laube et al., Finding REMO-detecting relative motion patterns in geospatial lifelines, 201–214, (2004)[1].