In this paper is overlooked one of Wireless Sensor Network applications - object tracking, which consists of localization, and object tracking algorithms. Localization is used to determine objects location in 2D or 3D space trough use of trilateration – where are needed three base nodes, with known location and distances from each node to object, triangulation – where are needed three base nodes and incoming signals angle from object, or multilateration – where are needed more than three base nodes with known location and distances from object. Object tracking algorithms task is to track objects location, and sends location information to the end user of the network. Depending on the algorithm it is plausible to track location energo-efficiently – when some of the nodes are in sleep mode, but other are tracking object, or non-energo-efficiently – where all nodes are tracking object whether they can see object or not. Tracking algorithms were classified into three classes - tree, cluster and prediction – based algorithms. Main goal was to look at the most common algorithms in each class to be able to deduce in which situations to use the algorithms from appropriate class, and, furthermore, suggest criteria that could be taken into account for algorithm comparison. In paper were used researches of recent year researches on wireless sensor networks. Work is concluded with main metrics which could be used to better compare algorithms, but in order to do that it is necessary to ensure a uniform start position, e.g. an equal number of nodes, the same environment in which WSN nodes operate, energy sources, etc. Acquired results could be used to develop new tracking algorithm or improve an existing algorithm that would not have the reviewed algorithms negative aspects.