Ng Samantha, Fakih Adel, Fourney Adam, Poupart Pascal, Zelek John
University of Waterloo.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:1220-5. doi: 10.1109/IEMBS.2009.5333085.
Cognitive assistance of a rollator (wheeled walker) user tends to reduce the attentional capacity of the user and may impact her stability. Hence, it is important to understand and track the pose of rollator users before augmenting a rollator with some form of cognitive assistance. While the majority of current markerless vision systems focus on estimating 2D and 3D walking motion in the sagittal plane, we wish to estimate the 3D pose of rollator users' lower limbs from observing image sequences in the coronal (frontal) plane. Our apparatus poses a unique set of challenges: a single monocular view of only the lower limbs and a frontal perspective of the rollator user. Since motion in the coronal plane is relatively subtle, we explore multiple cues within a Bayesian probabilistic framework to formulate a posterior estimate for a given subject's leg limbs. In this work, our focus is on evaluating the appearance model (the cues). Preliminary experiments indicate that texture and colour cues conditioned on the appearance of a rollator user outperform more general cues, at the cost of manually initializing the appearance offline.
助行器（带轮步行器）使用者的认知辅助往往会降低使用者的注意力，并可能影响其稳定性。因此，在为助行器增加某种形式的认知辅助之前，了解并跟踪助行器使用者的姿势非常重要。虽然当前大多数无标记视觉系统专注于估计矢状面内的二维和三维步行运动，但我们希望通过观察冠状（额状）面中的图像序列来估计助行器使用者下肢的三维姿势。我们的设备带来了一系列独特的挑战：仅对下肢的单目视图以及助行器使用者的正面视角。由于冠状面内的运动相对细微，我们在贝叶斯概率框架内探索多种线索，以制定给定受试者腿部的后验估计。在这项工作中，我们的重点是评估外观模型（线索）。初步实验表明，以助行器使用者外观为条件的纹理和颜色线索比更一般的线索表现更好，但代价是需要离线手动初始化外观。
