Active Image Labeling and Its Application to Facial Action Labeling

For many tasks in computer vision, it is very important to produce the groundtruth data. At present, this is mostly done manually. Manual data labeling is labor-intensive and prone to the human errors. The training data it produces often lacks in both quantity and quality. Fully automatic data labeling, on the other hand, is not feasible and reliable. In this paper, we propose an interactive image labeling technique for efficient and accurate data labeling. The proposed technique includes two parts: an automatic labeling part and a human intervention part. Constructed on a Bayesian Network, the automatic image labeler produces an initial labeling of the image. A person then examines the initial labeling and makes some minor corrections. The selected human corrections and the image measurements are then integrated by the Bayesian Network framework to produce a refined labeling. To minimize the human involvement, an active user feedback strategy is developed, through which the optimal us...

• Type: Conference
• Year: 2008
• Where: ECCV
• Authors: Lei Zhang, Yan Tong, Qiang Ji
• Keywords: Computer Vision, Data Labeling, ECCV 2008, Initial Labeling, Manual Data Labeling