實驗環境的噪音表現下的設置在動物行為及心理學的研究中是一個相當重要的因素，而在行為量測環境中的噪音，一般是由空調設備、實驗設備或是人為所產生，傳統的自動化影像追蹤系統每一個量測平台都需要一台個人電腦作為資料分析及儲存用，這對於需要環境控制的實驗應用是吵雜而且不方便的。
而醫藥或行為量測的應用中常常需要監測小動物的行為反應，一般而言，動物通常是被放在一個實驗箱中做實驗，並利用許多感測方法去量測動物在實驗箱中的移動行為，現在的研究方法需要長時間並且同時監測很多個實驗箱，可是現有市售的量測系統都需要一台個人電腦，這樣的系統在同時大量監控的實驗中會變得相當的複雜、昂貴以及增加功率消耗而浪費能源。
本文提出一個可以應用在獨立運作及長時間紀錄系統上的影像追蹤演算法，這個追蹤演算法的計算的速度很快、資料儲存很小及硬體的需求很低，這個可以獨立運作的系統結合了FPGA和MCU這兩個主要元件，可以同時自動追蹤動物行為及儲存追蹤的資訊到SD card中，這個系統的影像解析度為640*480 pixels及色彩解析度為16 bits，追蹤結果的更新頻率為每秒30筆資料，由於只有追蹤到的座標資料被儲存，因此儲存的資料量很小。本系統的追蹤演算法是使用物體上特殊的顏色作為我們追蹤的依據，所以可以在複雜的背景中做到多目標追蹤，而且我們使用的顏色空間為YCbCR，所以比較不受亮度的干擾，這意謂著本系統可以在一定的亮度改變的環境下追蹤物體。而且本系統主要是由積體電路所組成，沒有其他的機械結構運轉的聲音如風扇、馬達等等，所以本系統操作時是完全沒有聲音的，非常適合應用在噪音控制的實驗環境。

The acoustic environment is an important variable in studies with animal behavior and psychology. Noise represents an important factor in laboratory settings. Noise of moderate intensity is produced by air conditioning devices and experimental equipment. Traditional automated video tracking systems require one personal computer per monitoring platform, which are noisy and inconvenient for large laboratory applications.
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. But conventional systems require one personal computer per monitoring platform, which is too complex, expensive and increase power consumption for large laboratory applications.
This paper presents a simplified video tracking algorithm for long-term recording using 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 combination of FPGA and MCU simultaneously and automatically performs tracking and saving acquired data to a SD card. The proposed system is designed for video collected at a 640×480 pixels with 16 bits color resolution. The tracking result is updated every 30 frames per second and only the locomotive data are stored. Therefore, the data storage requirements could be minimized. In addition, detection via the designed algorithm uses the Y (luminance component), Cb (blue-difference chrominance component) and Cr (red-difference chrominance component) value of a colored marker affixed to the target to define the tracked position and allows multi-object tracking against complex backgrounds. The proposed system can track animal’s locomotion totally noiseless operating. Preliminary experiment showed that such tracking information stored by the portable and stand-alone system could provide comprehensive information on the animal’s activity.

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