  For humans, object detection, recognition, and tracking are innate. These
provide the ability for human to perceive their environment and objects within
their environment. This ability however doesn't translate well in computers. In
Computer Vision and Multimedia, it is becoming increasingly more important to
detect, recognize and track objects in images and/or videos. Many of these
applications, such as facial recognition, surveillance, animation, are used for
tracking features and/or people. However, these tasks prove challenging for
computers to do effectively, as there is a significant amount of data to parse
through. Therefore, many techniques and algorithms are needed and therefore
researched to try to achieve human like perception. In this literature review,
we focus on some novel techniques on object detection and recognition, and how
to apply tracking algorithms to the detected features to track the objects'
movements.
