Burnout Recognition for Call Center Agents by Using Skin Color Detection with Hand Poses

Call centers have been expanding and they have influence on activation in various markets increasingly. A call center’s work is known as one of the most demanding and stressful jobs. In this paper, we propose the fatigue detection system in order to detect burnout of call center agents in the case of a neck pain and upper back pain. Our proposed system is based on the computer vision technique combined skin color detection with the Viola-Jones object detector. To recognize the gesture of hand poses caused by stress sign, the YCbCr color space is used to detect the skin color region including face and hand poses around the area related to neck ache and upper back pain. A cascade of clarifiers by Viola-Jones is used for face recognition to extract from the skin color region. The detection of hand poses is given by the evaluation of neck pain and upper back pain by using skin color detection and face recognition method. The system performance is evaluated using two groups of dataset created in the laboratory to simulate call center environment. Our call center agent burnout detection system has been implemented by using a web camera and has been processed by MATLAB. From the experimental results, our system achieved 96.3% for upper back pain detection and 94.2% for neck pain detection.

• El Sayed A. Sharara
• A. Tsuji
• K. Terada

• Call center agents
• fatigue
• skin color detection
• face recognition.

[1] Michel Rod, Nicholas J. Ashill, (2013) "The impact of call center stressors on inbound and outbound call center agent burnout", Managing Service Quality: An International Journal, Vol. 23 Issue: 3, pp.245-264.
[2] Michel Rod, Peter Thirkell, Janet Carruthers, (2009) "Job resourcefulness, symptoms of burnout and service recovery performance: an examination of call centre frontline employees", Journal of Services Marketing, Vol. 23 Issue: 5, pp.338-350.
[3] Lewig, Karey A., and Maureen F. Dollard. "Emotional dissonance, emotional exhaustion and job satisfaction in call centre workers." European Journal of Work and Organizational Psychology 12.4 (2003): 366-392.
[4] Grebner, Simone, et al. "Working conditions, well-being, and job-related attitudes among call centre agents." European Journal of Work and Organizational Psychology 12.4 (2003): 341-365.
[5] Castanheira, Filipa, and Maria José Chambel. "Reducing burnout in call centers through HR practices." Human Resource Management 49.6 (2010): 1047-1065.
[6] Zapf, Dieter, et al. "Emotion work and job stressors and their effects on burnout." Psychology & Health 16.5 (2001): 527-545.
[7] Markan Lopar and Slobodan Ribaric, An Overview and Evaluation of Various Face and Eyes Detection Algorithma for Driver Fatigue Monitoring Systems”, CCVW, pp. 15-18, Sept 2013.
[8] Paul Viola and Michael Jones, “Rapid Object Detection using a Booted Cascade of Simple Features”, IEEE CVPR, vol. 1, pp. 511-518, 2001
[9] P. Kakumanu, S. Makrogiannis and N. Bourbakis, “Survey of skin-color modeling and detection methods”, Pattern Recognition 40, pp. 1106-1122, 2007.
[10] Yen-Hui lin, Chih- Yong chen, shih-Yi LU and Yu-chao Lin, “Visual fatigue during VDT work: Effects of time based and environment based conditions”, ELSEVIER, pp. 487-492, 2008.
[11] Yun Hua Chen, Weijian Liu, Ling zhang,Mingyu Yan,Yanjun Zeng, “Hybrid facial image feature extraction and recognition for non-invasive chronic fatigue syndrome diagnosis”, ELSEVIER, pp. 30-39, 2015.
[12] El-Sayed, A. Sharara and A. Tsuji K. Terada “A comparison of Viola-Jones Object detector and Skin- color Detection for Observing VDT Worker Fatigue”, SJCIEE, 13-8, pp.159 Sept. 2016.
[13] El-Sayed, A. Sharara and A. Tsuji K. Terada “Detecting upper back pain for VDT workers using viola-jones object detector and skin color detection”, IWFCV2017 Feb. 2017.