Constraint-Based Visual Hand Gesture Analysis

基于约束的视觉手势分析

• 批准号: 0138965
• 负责人: Thomas Huang
• 金额: $ 37.98万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-01 至 2006-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0138965&HistoricalAwards=false
• 关键词: Constraint; Based; Visual; Hand; Gesture

Visual hand/finger tracking and analysis has many important potential applications, including human-computer interaction, rehabilitation, and the recognition of sign languages. The major obstacle to real-time visual hand/finger tracking is the huge dimensionality of the configuration space. E.g., using the finger joint angles to represent the posture, the number of degrees of freedom is about 27. Tracking in this high- dimensional space is computationally impossible. However, finger movement is highly constrained. We propose to use a 3D model-based approach, where the model will include both posture and motion constraints. Tracking is done by matching the image of the real hand and that of the predicted view of the hand from the 3D model. The crux is to use the constraints to reduce the search time. By the end of the proposed period, we expect to have a good constraint representation and a good real-time hand/finger tracking algorithm, and to have demonstrated real-time tracking for the application of virtual object manipulation.

视觉手/手指跟踪和分析具有许多重要的潜在应用，包括人类计算机的互动，康复和标志语言的识别。实时视觉手/手指跟踪的主要障碍是配置空间的巨大维度。 例如，使用手指关节角来表示姿势，自由度的数量约为27。在此高维空间中跟踪在计算上是不可能的。 但是，手指运动受到高度限制。 我们建议使用基于3D模型的方法，该方法将同时包括姿势和运动约束。 跟踪是通过匹配真实手的图像以及3D模型中手的预测视图的图像来完成的。 关键是要使用约束来减少搜索时间。 到拟议时期结束时，我们希望具有良好的约束表示形式和良好的实时手/手指跟踪算法，并展示了用于应用虚拟对象操作的实时跟踪。