mlsanityData to 14 Oct 2026

Crime scene classification from skeletal trajectory analysis in surveillance settings

arXiv 2207.01687 ↗First posted 4 Jul 2022cs.CVcited by 3

Not on the map. Why?

Abstract (arXiv)

Video anomaly analysis is a core task actively pursued in the field of computer vision, with applications extending to real-world crime detection in surveillance footage. In this work, we address the task of human-related crime classification. In our proposed approach, the human body in video frames, represented as skeletal joints trajectories, is used as the main source of exploration. First, we introduce the significance of extending the ground truth labels for HR-Crime dataset and hence, propose a supervised and unsupervised methodology to generate trajectory-level ground truth labels. Next, given the availability of the trajectory-level ground truth, we introduce a trajectory-based crime classification framework. Ablation studies are conducted with various architectures and feature fusion strategies for the representation of the human trajectories. The conducted experiments demonstrate the feasibility of the task and pave the path for further research in the field.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 14 of its 49 references that are in the map. First posted on arXiv 4 Jul 2022.

Builds on

14 of 49 references.

References · 14

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2018Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labelscited by 997
  3. 2018Real-world Anomaly Detection in Surveillance Videoscited by 577
  4. 2018GANomaly: Semi-Supervised Anomaly Detection via Adversarial Trainingcited by 409
  5. 2015LSTM: A Search Space Odysseycited by 316
  6. 2016Learning Temporal Regularity in Video Sequencescited by 254
  7. 2016LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detectioncited by 215
  8. 2019Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videoscited by 104
  9. 2019Skip-GANomaly: Skip Connected and Adversarially Trained Encoder-Decoder Anomaly Detectioncited by 100
  10. 2020A Survey of Single-Scene Video Anomaly Detectioncited by 88
  11. 2020Any-Shot Sequential Anomaly Detection in Surveillance Videoscited by 34
  12. 2020Online Anomaly Detection in Surveillance Videos with Asymptotic Bounds on False Alarm Ratecited by 22
2 more
  1. 2019DC-SPP-YOLO: Dense Connection and Spatial Pyramid Pooling Based YOLO for Object Detectioncited by 14
  2. 2021HR-Crime: Human-Related Anomaly Detection in Surveillance Videoscited by 5

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 2.

3 papers.

  1. 2023Prompt-Guided Zero-Shot Anomaly Action Recognition using Pretrained Deep Skeleton Featurescited by 21
  2. 2024Enhancing Human Action Recognition and Violence Detection Through Deep Learning Audiovisual Fusioncited by 1
  3. 2024DIFEM: Key-points Interaction based Feature Extraction Module for Violence Recognition in Videoscited by 0