Video tracking algorithm of long-term experiment using stand-alone recording system.

Many medical and behavioral applications require the ability to monitor and quantify the behavior of small animals. In general these animals are confined in small cages. Often these situations involve very large numbers of cages. Modern research facilities commonly monitor simultaneously thousands of animals over long periods of time. However, conventional systems require one personal computer per monitoring platform, which is too complex, expensive, and increases power consumption for large laboratory applications. This paper presents a simplified video tracking algorithm for long-term recording using a stand-alone system. The feature of the presented tracking algorithm revealed that computation speed is very fast data storage requirements are small, and hardware requirements are minimal. The stand-alone system automatically performs tracking and saving acquired data to a secure digital card. The proposed system is designed for video collected at a 640 x 480 pixel with 16 bit color resolution. The tracking result is updated every 30 frames/s. Only the locomotive data are stored. Therefore, the data storage requirements could be minimized. In addition, detection via the designed algorithm uses the Cb and Cr values of a colored marker affixed to the target to define the tracked position and allows multiobject tracking against complex backgrounds. Preliminary experiment showed that such tracking information stored by the portable and stand-alone system could provide comprehensive information on the animal's activity.