Purdue University Graduate School
PurdueThesis_CrimeDetectionFromPre_CrimeVideoAnalysis_SedatKilic-5.pdf (10.53 MB)

Crime Detection From Pre-crime Video Analysis

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posted on 2024-06-03, 18:30 authored by Sedat KilicSedat Kilic

his research investigates the detection of pre-crime events, specifically targeting behaviors indicative of shoplifting, through the advanced analysis of CCTV video data. The study introduces an innovative approach that leverages augmented human pose and emotion information within individual frames, combined with the extraction of activity information across subsequent frames, to enhance the identification of potential shoplifting actions before they occur. Utilizing a diverse set of models including 3D Convolutional Neural Networks (CNNs), Graph Neural Networks (GNNs), Recurrent Neural Networks (RNNs), and a specially developed transformer architecture, the research systematically explores the impact of integrating additional contextual information into video analysis.

By augmenting frame-level video data with detailed pose and emotion insights, and focusing on the temporal dynamics between frames, our methodology aims to capture the nuanced behavioral patterns that precede shoplifting events. The comprehensive experimental evaluation of our models across different configurations reveals a significant improvement in the accuracy of pre-crime detection. The findings underscore the crucial role of combining visual features with augmented data and the importance of analyzing activity patterns over time for a deeper understanding of pre-shoplifting behaviors.

The study’s contributions are multifaceted, including a detailed examination of pre-crime frames, strategic augmentation of video data with added contextual information, the creation of a novel transformer architecture customized for pre-crime analysis, and an extensive evaluation of various computational models to improve predictive accuracy.


Degree Type

  • Doctor of Philosophy


  • Computer and Information Technology

Campus location

  • Indianapolis

Advisor/Supervisor/Committee Chair

Mihran Tuceryan

Additional Committee Member 2

Jiang Yu Zheng

Additional Committee Member 3

Gavriil Tsechpenakis

Additional Committee Member 4

Arjan Durresi