Minimal-latency human action recognition using reliable-inference

作者：Davis JW^*; Tyagi A

来源：Image and Vision Computing, 2006, 24(5): 455-472.

DOI：10.1016/j.imavis.2006.01.012

• action recognition
• reliable-inference
• MAP
• video analysis

We present a probabilistic reliable-inference framework to address the issue of rapid detection of human actions with low error rates. The approach determines the shortest video exposures needed for low-latency recognition by sequentially evaluating a series of posterior ratios for different action classes. If a subsequence is deemed unreliable or confusing, additional video frames are incorporated until a reliable classification to a particular action can be made. Results are presented for multiple action classes and subsequence durations, and are compared to alternative probabilistic approaches. The framework provides a means to accurately classify human actions using the least amount of temporal information.

• 出版日期2006-5-1