1,102 research outputs found
Circulant temporal encoding for video retrieval and temporal alignment
We address the problem of specific video event retrieval. Given a query video
of a specific event, e.g., a concert of Madonna, the goal is to retrieve other
videos of the same event that temporally overlap with the query. Our approach
encodes the frame descriptors of a video to jointly represent their appearance
and temporal order. It exploits the properties of circulant matrices to
efficiently compare the videos in the frequency domain. This offers a
significant gain in complexity and accurately localizes the matching parts of
videos. The descriptors can be compressed in the frequency domain with a
product quantizer adapted to complex numbers. In this case, video retrieval is
performed without decompressing the descriptors. We also consider the temporal
alignment of a set of videos. We exploit the matching confidence and an
estimate of the temporal offset computed for all pairs of videos by our
retrieval approach. Our robust algorithm aligns the videos on a global timeline
by maximizing the set of temporally consistent matches. The global temporal
alignment enables synchronous playback of the videos of a given scene
Action Recognition in Videos: from Motion Capture Labs to the Web
This paper presents a survey of human action recognition approaches based on
visual data recorded from a single video camera. We propose an organizing
framework which puts in evidence the evolution of the area, with techniques
moving from heavily constrained motion capture scenarios towards more
challenging, realistic, "in the wild" videos. The proposed organization is
based on the representation used as input for the recognition task, emphasizing
the hypothesis assumed and thus, the constraints imposed on the type of video
that each technique is able to address. Expliciting the hypothesis and
constraints makes the framework particularly useful to select a method, given
an application. Another advantage of the proposed organization is that it
allows categorizing newest approaches seamlessly with traditional ones, while
providing an insightful perspective of the evolution of the action recognition
task up to now. That perspective is the basis for the discussion in the end of
the paper, where we also present the main open issues in the area.Comment: Preprint submitted to CVIU, survey paper, 46 pages, 2 figures, 4
table
Twofold Video Hashing with Automatic Synchronization
Video hashing finds a wide array of applications in content authentication,
robust retrieval and anti-piracy search. While much of the existing research
has focused on extracting robust and secure content descriptors, a significant
open challenge still remains: Most existing video hashing methods are fallible
to temporal desynchronization. That is, when the query video results by
deleting or inserting some frames from the reference video, most existing
methods assume the positions of the deleted (or inserted) frames are either
perfectly known or reliably estimated. This assumption may be okay under
typical transcoding and frame-rate changes but is highly inappropriate in
adversarial scenarios such as anti-piracy video search. For example, an illegal
uploader will try to bypass the 'piracy check' mechanism of YouTube/Dailymotion
etc by performing a cleverly designed non-uniform resampling of the video. We
present a new solution based on dynamic time warping (DTW), which can implement
automatic synchronization and can be used together with existing video hashing
methods. The second contribution of this paper is to propose a new robust
feature extraction method called flow hashing (FH), based on frame averaging
and optical flow descriptors. Finally, a fusion mechanism called distance
boosting is proposed to combine the information extracted by DTW and FH.
Experiments on real video collections show that such a hash extraction and
comparison enables unprecedented robustness under both spatial and temporal
attacks.Comment: submitted to Image Processing (ICIP), 2014 21st IEEE International
Conference o
Automatic semantic video annotation in wide domain videos based on similarity and commonsense knowledgebases
In this paper, we introduce a novel framework for automatic Semantic Video Annotation. As this framework detects possible events occurring in video clips, it forms the annotating base of video search engine. To achieve this purpose, the system has to able to operate on uncontrolled wide-domain videos. Thus, all layers have to be based on generic features.
This framework aims to bridge the "semantic gap", which is the difference between the low-level visual features and the human's perception, by finding videos with similar visual events, then analyzing their free text annotation to find a common area then to decide the best description for this new video using commonsense knowledgebases.
Experiments were performed on wide-domain video clips from the TRECVID 2005 BBC rush standard database. Results from these experiments show promising integrity between those two layers in order to find expressing annotations for the input video. These results were evaluated based on retrieval performance
ARCHANGEL: Tamper-proofing Video Archives using Temporal Content Hashes on the Blockchain
We present ARCHANGEL; a novel distributed ledger based system for assuring
the long-term integrity of digital video archives. First, we describe a novel
deep network architecture for computing compact temporal content hashes (TCHs)
from audio-visual streams with durations of minutes or hours. Our TCHs are
sensitive to accidental or malicious content modification (tampering) but
invariant to the codec used to encode the video. This is necessary due to the
curatorial requirement for archives to format shift video over time to ensure
future accessibility. Second, we describe how the TCHs (and the models used to
derive them) are secured via a proof-of-authority blockchain distributed across
multiple independent archives. We report on the efficacy of ARCHANGEL within
the context of a trial deployment in which the national government archives of
the United Kingdom, Estonia and Norway participated.Comment: Accepted to CVPR Blockchain Workshop 201
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