Object detection is a fundamental step in most of the video analysis applications. There are many research challenges involved in automatic object detection, depending on different scenarios. The most prevalent application of object detection is in the field of multimedia surveillance. In this talk we will discuss the common problems in the object detection in a surveillance video. Further, we will discuss the Gaussian Mixture Model (GMM) based object detection method. While object detection is the basic step of video analysis, higher level semantic interpretation of the scene requires trajectory information. Most of the suspicious event detection methods use tracking as the basic building block. In the second part of the talk, we will discuss particle filter based method of object tracking. To summarize, the aim of the talk is two-fold: (1) Discuss common problems in object detection and tracking (2) Hands on experience of how to use classical methods of GMM and particle filtering in problem solving.