Title: Multi-Camera Trajectory Forecasting (MCTF) using Shallow Learning

Abstract:

The objective of MCTF is to predict the trajectory of a moving object across a network of cameras. The existing approach (Styles et al) tracks one object across multiple cameras. However, its use for surveillance applications is limited. There exist robust object-tracking and prediction methods for single cameras, however they are not easily scaled for a network of cameras. We address these shortcomings by proposing a shallow-learning-based MCTF model with a location-tensor-based framework which would represent the location of objects across multiple cameras using the position of their bounding boxes over time. The model shall learn to predict the movement of the bounding boxes across the network of cameras in an image-agnostic way. We will discuss some techniques of shallow learning which help us accomplish this task.