Mentor: Salman Khokhar

Action Recognition in Crowds Week 7

This Week…

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

Next Week…

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

Next Next Week…

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