Proceedings ArticleDOI
Moving object tracking using Laplacian-DCT based perceptual hash
Sandeep Singh Sengar,Susanta Mukhopadhyay +1 more
- pp 2345-2349
TLDR
This work presents a novel and effective method to track moving objects under a static background that applies the Laplacian operator on the selected target objects for sharpening and edge detection and computes perceptual hash of a target object.Abstract:
Moving-object tracking is one of the basic and hot research domains in the computer vision area. This work presents a novel and effective method to track moving objects under a static background. Proposed method first executes the pre-processing tasks to remove noise from video frames. Then, with the help of rectangular window, we select the target object region in the first video frame (reference frame). Next, it applies the Laplacian operator on the selected target objects for sharpening and edge detection. The algorithm then applies the DCT and selects the few high energy coefficients. Subsequently, it computes the perceptual hash of the selected target objects with the help of mean of all the AC values of the block. Using perceptual hash of a target object, we find the similar object in subsequent frames of the video. The proposed method is correct for tracking the moving target object with varying object size and significant amount of noise. This work has been formulated, implemented and tested on real indoor-outdoor video sequences and the results are found to be adequate as it proved from the performance evaluation.read more
Citations
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Journal ArticleDOI
Moving object detection based on frame difference and W4
TL;DR: An approach to segment the moving objects using both the frame differencing and W4 algorithm to overcome the above problems and the effectiveness of this approach in comparison with existing techniques is demonstrated.
Journal ArticleDOI
Detection of moving objects based on enhancement of optical flow
TL;DR: This paper has efficiently detected the moving objects by computing the optical flow between three consecutive frames by implementing an adaptive thresholding post-processing step and using morphological operation on the equalized output.
Journal ArticleDOI
Motion segmentation-based surveillance video compression using adaptive particle swarm optimization
TL;DR: A hybrid video compression approach with the help of foreground motion compensation for smart surveillance, which works effectively by including the advantages of both block-based and object-based coding techniques as well as reducing the drawbacks of both.
Journal ArticleDOI
Moving object detection using statistical background subtraction in wavelet compressed domain
TL;DR: A statistical background subtraction based motion segmentation method in a compressed transformed domain employing wavelet that employs the weighted-mean and weighted-variance based background subtracted operations only on the detailed components of the wavelet transformed frame to reduce the computational complexity.
Journal ArticleDOI
Motion detection using block based bi-directional optical flow method
TL;DR: The experimental results and quantitative evaluation establish that the proposed Display Omitted Optical flow based moving object detection algorithm achieves effective and efficient results than other existing methods.
References
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A Database and Evaluation Methodology for Optical Flow
TL;DR: This paper proposes a new set of benchmarks and evaluation methods for the next generation of optical flow algorithms and analyzes the results obtained to date to draw a large number of conclusions.
Book
Kalman Filtering: Theory and Practice Using MATLAB
TL;DR: Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering and appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.
Journal ArticleDOI
Support vector tracking
TL;DR: Support Vector Tracking integrates the Support Vector Machine (SVM) classifier into an optic-flow-based tracker and maximizes the SVM classification score to account for large motions between successive frames.
Journal ArticleDOI
Multicamera People Tracking with a Probabilistic Occupancy Map
TL;DR: It is demonstrated that the generative model can effectively handle occlusions in each time frame independently, even when the only data available comes from the output of a simple background subtraction algorithm and when the number of individuals is unknown a priori.
Proceedings ArticleDOI
Stable multi-target tracking in real-time surveillance video
Ben Benfold,Ian Reid +1 more
TL;DR: This work presents a multi-target tracking system that is designed specifically for the provision of stable and accurate head location estimates and uses a more principled approach based on a Minimal Description Length (MDL) objective which accurately models the affinity between observations.