INSTITUTIONAL DIGITAL REPOSITORY

Browsing by Author "Kumari, P."

Browsing by Author "Kumari, P."

Sort by: Order: Results:

  • An adaptive framework for anomaly detection in time-series audio-visual data 
    Kumari, P.; Saini, M. (2022-07-15)
    Anomaly detection is an integral part of a number of surveillance applications. However, most of the existing anomaly detection models are statically trained on pre-recorded data from a single source, thus making multiple ...
  • ALPS 1.0: towards automated lecture profiling system 
    Kumari, P.; Jain, P.; Sahay, S.; Tian, G.; Saini, M. (2020-01-02)
    In this paper, we propose a multimedia framework to automatically profile student-teacher interaction during a lecture using a mobile. We employ audio, video, and text analysis to derive a subset of attributes that ...
  • An audio-seismic fusion framework for human activity recognition in an outdoor environment 
    Choudhary, P.; Kumari, P.; Goel, N.; Saini, M. (2022-11-11)
    Human activity recognition has a significant impact on people’s daily lives. The need to infer human activities is prominent in many human-centric applications, such as healthcare and individual assistance. In this paper, ...
  • Dynamic scheduling of an autonomous PTZ camera for effective surveillance 
    Kumari, P.; Nandyala, N.; Teja, A. K. S.; Goel, N.; Saini, M. (2021-06-19)
    PTZ cameras can be an effective replacement for multiple camera networks with their pan-tilt-zoom capability. However, the state of the art scheduling method for the PTZ cameras focuses mainly on tracking, not on coverage. ...
  • Multimodal drunk density estimation for safety assessment 
    Kumari, P.; Singh, M.; Saini, M. (2021-08-26)
    Drinking alcohol in excess leads to lower selfconsciousness, damaging a persons judgment and thus enhances risk of aggressive behavior. It leads to various problems like social abuse, violence, crime, and road accidents. Hence, ...
  • Multivariate adaptive gaussian mixture for scene level anomaly modeling 
    Kumari, P.; Saini, M. (2021-06-20)
    Scene changes that typically occur in a real-world setting degrade anomaly detection performance over the long run. Most of the existing methods ignore the challenge of temporal concept drift in video surveillance. In ...
  • Situational anomaly detection in multimedia data under concept drift 
    Kumari, P. (2022-08-21)
    Anomaly detection has been a very challenging and active area of research for decades, particularly for video surveillance. However, most of the works detect predefined anomaly classes using static models. These frameworks ...