THRESHOLD DYNAMIC TIME WARPING FOR SPATIAL ACTIVITY RECOGNITION
Daniel Erwin Riedel, Svetha Venkatesh, Wanquan Liu · Deakin Research Online (Deakin University) · 2007
Abstract. Non-invasive spatial activity recognition is a difficult task, compli-cated by variation in how the same activities are conducted and furthermore by noise introduced by video tracking procedures. In this paper we propose an al-gorithm based on dynamic time warping (DTW) as a viable method with which to quantify segmented spatial activity sequences from a video tracking system. DTW is a widely used technique for optimally aligning or warping temporal se-quences through minimisation of the distance between their components. The proposed algorithm threshold DTW (TDTW) is capable of accurate spatial sequence distance quantification and is shown using a three class spatial data set to be more robust and accurate than DTW and the discrete hidden markov model (HMM). We also evaluate the application of a band dynamic program-ming (DP) constraint to TDTW in order to reduce extraneous warping between sequences and to reduce the computation complexity of the approach. Results show that application of a band DP constraint to TDTW improves runtime performance significantly, whilst still maintaining a high precision and recall.