Rameswar Panda

I am currently (2014-) a Ph.D. student in Dept. of ECE at UC Riverside. My advisor is Prof. Amit K. Roy-Chowdhury and I work in Video Computing Group on developing efficient algorithms for summarizing big visual data.

I obtained my M.S. in Computer Engineering from Jadavpur University (India) in 2013 supervised by Prof. Ananda S. Chowdhury. During my masters, I have worked on some interesting problems in graph theory and pattern recognition. I have also spent some amazing time at Siemens Corporate Research working on weakly supervised object localization and some problems pertinent to heavy engineering industries (defect detection).

Email / Curriculum Vitae / Google scholar / Linkedin / Facebook




Research

It is an impressive yet alarming fact that there is far more video being captured—by consumers, scientists, defense analysts, and others—than can ever be watched or browsed efficiently. The goal of my research is to develop efficient and scalable algorithms to summarize the visual world (i.e., videos and image collections).

My research interests are in Computer Vision, Machine Learning, Multimedia Computing and Pattern Recognition. Specifically, I am interested in exploring different machine learning techniques (Sparse Coding, Deep Learning and Graph Clustering) to solve several challenging problems in summarizing and segmenting videos. I also worked on person re-identification in video surveillance, weakly supervised object localization and interesting defect/anomoly detection problems in non-destructive testing.

News

2017
  • Paper on Multi-View Surveillance Video Summarization accepted to IEEE Trans. on Multimedia.
  • Paper on Multi-Video Summarization accepted to IEEE Trans. on Image Processing.
  • Paper on Open World Person Re-id accepted at CVPR 2017 (Spotlight).
  • Paper on Collaborative Video Summarization accepted at CVPR 2017.
  • Paper on Topic-oriented Video Summarization accepted at ICASSP 2017.
  • Paper on Multi-view Spectral Clustering accepted to IEEE Trans. on Cybernatics.
  • 2016
  • Research Intern with Computer Vision team at Siemens Corporate Research, Princeton.
  • Paper on Continuous Adaptation of Person Identification Models accepted to Elsevier CVIU.
  • Journal Publications

    Multi-View Surveillance Video Summarization via Joint Embedding and Sparse Optimization
    Rameswar Panda, Amit K. Roy-Chowdhury
    IEEE Transactions on Multimedia (TMM), 2017 (In Press)
    This paper extends our ICPR 2016 paper providing new theoretical insights with a joint optimization and experimenting on spatio-temporal features and datasets.
    Diversity-aware Multi-Video Summarization
    Rameswar Panda, Niluthpol C. Mithun, Amit K. Roy-Chowdhury
    IEEE Transactions on Image Processing (TIP), 2017 (In Press)
    Extension of our ICASSP 2017 paper. We propose a new generalized sparse optimization framework for summarizing multiple videos generated from a video search or from a multi-view camera network.
    Nystrom approximated temporally constrained multi-similarity spectral clustering approach for movie scene detection
    Rameswar Panda, Sanjay K. Kuanar, Ananda S. Chowdhury
    IEEE Transactions on Cybernetics (TCYB), 2017
    We present a fast solution for movie scene detection using Nystrom approximated multi-similarity spectral clustering with a temporal integrity constraint.
    Continuous Adaptation of Multi-Camera Person Identification Models through Sparse Non-redundant Representative Selection
    Abir Das, Rameswar Panda, Amit K. Roy-Chowdhury
    Computer Vision and Image Understanding (CVIU), 2016
    We addressed the problem of online learning of identification systems where unlabeled data comes in small minibatches, with human in the loop.
    Video Key frame Extraction through Dynamic Delaunay Clustering with a Structural Constraint
    Sanjay K. Kuanar, Rameswar Panda, Ananda S. Chowdhury
    Journal of Visual Communication and Image Representation (JVCIR), 2013
    This paper extends our ICPR 2012 paper providing new theoretical insights and experimenting on more features and datasets.

    Selected Conference Publications

    (see my Google Scholar for the full list of papers)
    Weakly Supervised Summarization of Web Videos
    Rameswar Panda, Abir Das, Ziyan Wu, Jan Ernst, Amit K. Roy-Chowdhury
    International Conference on Computer Vision (ICCV), 2017
    We introduce a weakly supervised approach that requires only video-level annotation for summarizing web videos.
    Unsupervised Adaptive Re-identification in Open World Dynamic Camera Networks
    Rameswar Panda, Amran Bhuiyan, Vittorio Murino, Amit K. Roy-Chowdhury
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
    We propose an unsupervised adaptation scheme for for re-identification models in a dynamic camera network where a new camera may be temporarily inserted into an existing system to get additional information.
    Collaborative Summarization of Topic-Related Videos
    Rameswar Panda, Amit K. Roy-Chowdhury
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
    This paper presents a collaborative video summarization approach that exploits visual context from a set of topic-related videos to extract an informative summary of a given video.
    Sparse Modeling for Topic-oriented Video Summarization
    Rameswar Panda, Amit K. Roy-Chowdhury
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017
    This paper presents a diversity-aware sparse optimization framework for summarizing topi-related videos generated from a video search.
    Video Summarization in a Multi-View Camera Network
    Rameswar Panda, Abir Das, Amit K. Roy-Chowdhury
    IEEE International Conference on Pattern Recognition (ICPR), 2016
    This paper presents a framework for summarizing multi-view videos by exploiting both intra- and inter-view content correlations in a joint embedding space.
    Embedded Sparse Coding for Summarizing Multi-View Videos
    Rameswar Panda, Abir Das, Amit K. Roy-Chowdhury
    IEEE International Conference on Image Processing (ICIP), 2016
    This paper presents a stochastic multi-view frame embedding based on KL diveregence to preserve correlations in multi-view learning.
    Generating Diverse Image Datasets with Limited Labeling
    Niluthpol C. Mithun, Rameswar Panda, Amit K. Roy-Chowdhury
    ACM International Conference on Multimedia (MM), 2016
    This paper presents a semi-supervised sparse coding framework to collect a diverse set of images with minimal human effort.
    Active Image Pair Selection for Continuous Person Re-identification
    Abir Das, Rameswar Panda, Amit K. Roy-Chowdhury
    IEEE International Conference on Image Processing (ICIP), 2015
    We present a continuous learning re-id system with a human in the loop.
    Scalable Video Summarization using Skeleton Graph and Random Walk
    Rameswar Panda, Sanjay K. Kuanar, Ananda S. Chowdhury
    IEEE International Conference on Pattern Recognition (ICPR), 2014
    This paper presents a video summarization framework which is scalable during both the analysis and the generation stages of video summarization.
    Video Storyboard Design using Delaunay Graphs
    Ananda S. Chowdhury, Sanjay K. Kuanar, Rameswar Panda, Moloy N. Das
    IEEE International Conference on Pattern Recognition (ICPR), 2012
    This paper uses dynamic Delunay grpah clustering for summarizing videos.

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