1. Mentor: Salman Khokhar Action Recognition in Crowds Week 7

2. Read papers on Dense Trajectory Features for Action Recognition  IDTF paper  Heng Wang, Cordelia Schmid. Action Recognition with Improved Trajectories. ICCV 2013 - IEEE International Conference on Computer Vision, Dec 2013, Sydney, Australia. IEEE, pp.3551-3558, 2013,.  The code utilized in this paper is the same one we use for feature extraction in our crowd videos  Uses MBH, HOF, HOG descriptors  Bag of words k-means clusters

3.  Continue reading the papers on feature extraction  Gain deeper understanding  Explore mathematics behind the theory  Test my dataset on segmentation code (extract features)  Utilize the Linux server  Understand the current code  Analyze results on the experiments

4.  End goal is to eventually improve feature extraction  Improve descriptor methods (better histograms)  Test changes on existing dataset  Focus on detecting temporal anomalies in features  Using human detections to track people across frames  Identifying features that represent change in pattern of their movement