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Register a new userAppearance based and Gesture Independent Model for Natural Human Hand Detection and Tracking
نموذج معتمد على المظهر و مستقل عن الإيماءات لاكتشاف اليد البشرية المجردة و ملاحقتها
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تتعدد البحوث و الدراسات العلمية التي تعمل على تحسين طريقة تفاعل الإنسان مع الآلة و جعلها أقرب إلى الأسلوب البشري في التفاعل سواء من خلال محاولة فهم الكلام أو الإيماءات أو حتى إشارات الدماغ, و لكن اعتماد الإنسان اعتماداً كبيراً على يديه في التفاعل مع بيئته المحيطة أعطى أهمية خاصة للبحوث التي تهتم بتعرف اليد و حركاتها و ملاحقتها. يقدم هذا البحث أسلوباً جديداً لتعرف يد بشرية تتحرك بشكل طبيعي أمام كاميرا رقمية عادية و ملاحقتها ضمن بيئة غير معروفة مسبقاً, بغض النظر عن وضعية الأصابع أو شكل اليد و دون الحاجة إلى ارتداء قّفازات أو معّلمات إضافية. تقوم الطريقة المقترحة بالتمييز بين اليد و الأجسام المتحركة الأخرى و خاصة الوجه عن طريق تحديد نقاط الفيديو المتحركة من لون الجلد البشري، و تطبيق مجموعة من المعايير المقترحة المعتمدة على معالجة صور الفيديو لتعرف الجسم الممثل لليد. قمنا بإجراء دراسة عملية لتقييم الأداء فضلاً عن تصميم تلفاز افتراضي يجري التفاعل معه باستخدام اليد المجردة كتطبيق مباشر على الطريقة المقترحة لمعرفة مدى فعاليتها و سهولة استعمالها بنظر المستخدمين. أظهرت النتائج إمكانية تعرف اليد بالزمن الحقيقي و بدقة تقارب % 99 ضمن ظروف إضاءة الغرفة الطبيعية.
Many researchers work on enhancement of Human Computer Interaction methods and try to make it more natural and intuitive. This includes researches in: understanding human languages, gestures recognition and brain signals recognition. But the heavy use of hands in human everyday life makes hand recognition and tracking researches very important. In this paper, we present a novel method to recognize and track a human hand moving in front of digital camera in an unknown environment without any constraints on fingers positions or hand gesture and with no need to wear any additional devices like gloves or markers. Our method can distinguish between hand and other moving objects especially faces, by applying some proposed criteria to determine which object is representing the hand. A practical study is performed to evaluate the performance of the proposed method. Hand interactive virtual TV is made as a realistic application to report users experiences. Results show that our proposed method can recognize human hand at real-time with 99% accuracy rate in normal indoors light.
References used
J. d. R. Millán, et al., "Brain-actuated interaction," Artificial intelligence, vol. 159, pp. 241-259, 2004
J. M. Rehg and T. Kanade, "Visual Tracking of High DOF Articulated Structures: an Application to Human Hand Tracking," presented at the Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II, 1994
K. Dorfmuller-Ulhaas and D. Schmalstieg, "Finger tracking for interaction in augmented environments," in Augmented Reality, 2001. Proceedings. IEEE and ACM International Symposium on, 2001, pp. 55-64
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