The idea of autonomous driving was merely just a dream about 5 years ago but now, with the advancements in technology, it has become prevalent. The aim of this thesis is to provide a low-cost approach for detecting and tracking moving objects from a moving platform. This could be used for an autonomous vehicle to automatically avoid moving objects. Our low cost approach will use a raspberry-pi processor board as computation platform and stereo cameras as sensors. The process of multiple moving objects detection is performed by initially calculating the disparity maps from the stereo image pairs. Following this is the generation of point cloud data from the disparity map which is followed by semantic segmentation and generation of object proposals. An EKF based tracker is used to track the moving objects across the frames.