A Rough Set theory based closed form object boundary detection method has been suggested in this paper. Most of the edge detection methods fail in getting closed boundary of objects of any shape present in the image. ...
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ISBN:
(纸本)9781479915880
A Rough Set theory based closed form object boundary detection method has been suggested in this paper. Most of the edge detection methods fail in getting closed boundary of objects of any shape present in the image. Active contour based methods are available to get such object boundaries. the Multiphase Chan-Vese Active Contour Method is one of the most popular of such techniques. However, it is constrained with number of objects present in the image. the granular processing using Rough Set method overcomes this constraint and provides a closed curve around the boundary of the objects. this information can further be utilized in selection of similar patches for various imageprocessing problems such as image Denoising, image Super-resolution, image Segmentation etc. the proposed boundary detection method has been tested in presence of noise also. the experimental results have shown on synthetic image as well as on MRI of human brain. the performance of proposed method is found to be encouraging.
In this paper, we propose a modified version of the standard proportional-derivative (PD) controller for biped locomotion. Our improvements stabilize the biped for high gain PD controllers. the main idea of our approa...
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ISBN:
(纸本)9781479915880
In this paper, we propose a modified version of the standard proportional-derivative (PD) controller for biped locomotion. Our improvements stabilize the biped for high gain PD controllers. the main idea of our approach involves applying corrective component to the existing framework, so that it prevents overshooting at high gains to stabilize the biped. We use pose control graphs to represent various gaits for the biped. We demonstrate with our improvements that the biped controller is stable while walking on irregular terrains. We also demonstrate that our formulation provides additional stability to the biped under minor impediments while in motion.
High-intensity activities in sports like basketball can result in fatigue without proper recovery. this study introduces a collaborative framework that leverages computervision (CV) and Machine Learning for evaluatin...
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ISBN:
(纸本)9798400710759
High-intensity activities in sports like basketball can result in fatigue without proper recovery. this study introduces a collaborative framework that leverages computervision (CV) and Machine Learning for evaluating jump landings and predicting athletic readiness by modelling Countermovement Jumps (CMJs) biomechanical aspects. Seventeen female collegiate basketball athletes of Sacred Heart University (SHU), CT, USA, participated in weekly CMJs over a 26-week season. through CV-driven semantic analysis of videos, the framework identifies the crucial initial contact and maximum flexion point during jump landings and extracts kinetic and kinematic features of the lower extremities. Next, an inferential analysis is conducted to understand the relationship between these features and the CMJ-driven reactive strength indexmodified (RSImod) score, which measures fatigue and athletic readiness. An XGBoost regressor, trained on the past week's data, then predicted the RSImod score for the following week, which resulted in an MSE of 0.020 and an R-2 of 0.892. Using SHapley Additive exPlanations (SHAP), the framework offers interpretable feedback, aiding coaches in creating personalised training programs and optimising athletic performance while minimising injury risks.
the spread of global smartphone market in the past decade has resulted in exponential growth of unstructured data, particularly in the form of multimedia, in the domain of social networking. Consequently, it has made ...
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ISBN:
(纸本)9781467385640
the spread of global smartphone market in the past decade has resulted in exponential growth of unstructured data, particularly in the form of multimedia, in the domain of social networking. Consequently, it has made data retrieval cumbersome, specially for the users. this has also posed as a major challenge in the development of new algorithms and technologies. this paper presents a context based search technique for personalized image retrieval, based on Logical Item-set Mining on image Hash-Tags given by the users. the tests were performed on Instagram image datasets of two different users, collected through a crawler and show promising results.
We present a novel dataset aimed at advancing danger analysis and assessment by addressing the challenge of quantifying danger in video content and identifying how human-like a Large Language Model (LLM) evaluator is ...
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ISBN:
(纸本)9798400710759
We present a novel dataset aimed at advancing danger analysis and assessment by addressing the challenge of quantifying danger in video content and identifying how human-like a Large Language Model (LLM) evaluator is for the same. this is achieved by compiling a collection of 100 YouTube videos featuring various events. Each video is annotated by human participants who provided danger ratings on a scale from 0 (no danger to humans) to 10 (life-threatening), with precise timestamps indicating moments of heightened danger. Additionally, we leverage LLMs to independently assess the danger levels in these videos using video summaries. We introduce Mean Squared Error (MSE) scores for multimodal meta-evaluation of the alignment between human and LLM danger assessments. Our dataset not only contributes a new resource for danger assessment in video content but also demonstrates the potential of LLMs in achieving human-like evaluations.
In this paper, a compressed domain blind watermarking scheme is proposed which embeds the watermark by altering the number of nonzero transform co-efficients (NNZ) of 4 x 4 transform blocks of the HEVC video sequence....
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ISBN:
(纸本)9781467385640
In this paper, a compressed domain blind watermarking scheme is proposed which embeds the watermark by altering the number of nonzero transform co-efficients (NNZ) of 4 x 4 transform blocks of the HEVC video sequence. To embed the watermark, firstly, temporally homogeneous blocks having relatively less motion are selected. In this work, watermark is inserted in the Intra (I) frame and the motion characteristics of the I frame has been determined using the motion information of the Inter (P or B) predicted frames of its close neighborhood. the watermark is embedded by altering the NNZ difference of 4 x 4 transform blocks in the consecutive intra predicted frames. A comprehensive set of experiments is carried out to show that the scheme is robust against re-compression attacks while maintaining a descent visual quality (PSNR), the bit increase rate (BIR) of the watermarked video.
images taken in bad weather conditions like haze and fog suffer from loss of contrast and color shift. the object radiance is attenuated in the atmosphere and the atmospheric light is added to the scene radiance creat...
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ISBN:
(纸本)9781467385640
images taken in bad weather conditions like haze and fog suffer from loss of contrast and color shift. the object radiance is attenuated in the atmosphere and the atmospheric light is added to the scene radiance creating a veil like semi-transparent layer called airlight. the methods proposed till now assumes that the atmospheric light is constant throughout the image domain, which may not be true always. Here we propose a method that works under the relaxed assumption that the color of atmospheric light is constant but its intensity may vary in the image. We use the color line model to estimate the contribution of airlight in each patch and interpolate at places where the estimate is not reliable. We apply reverse operation to recover the haze free image.
Withthe spread of smart phones capable of taking high-resolution photos and the development of high-speed mobile data infrastructure, digital visual media is becoming one of the most important forms of modern communi...
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ISBN:
(纸本)9789897584022
Withthe spread of smart phones capable of taking high-resolution photos and the development of high-speed mobile data infrastructure, digital visual media is becoming one of the most important forms of modern communication. Withthis development, however, also comes a devaluation of images as a media form withthe focus becoming the frequency at which visual content is generated instead of the quality of the content. In this work, an interactive system using image-abstraction techniques and an eye tracking sensor is presented, which allows users to experience diverting and dynamic artworks that react to their eye movement. the underlying modular architecture enables a variety of different interaction techniques that share common design principles, making the interface as intuitive as possible. the resulting experience allows users to experience a game-like interaction in which they aim for a reward, the artwork, while being held under constraints, e.g., not blinking. the conscious eye movements that are required by some interaction techniques hint an interesting, possible future extension for this work into the field of relaxation exercises and concentration training.
the video coding standard H.264 uses Contextbased Adaptive Variable Length Coding (CAVLC) as one of its entropy encoding techniques. this paper proposes VLSI architecture for CAVLC algorithm. the designed hardware mee...
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ISBN:
(纸本)9781479915880
the video coding standard H.264 uses Contextbased Adaptive Variable Length Coding (CAVLC) as one of its entropy encoding techniques. this paper proposes VLSI architecture for CAVLC algorithm. the designed hardware meets the required speed of H.264 without compromising the hardware cost. the CAVLC encoder works at a maximum clock frequency of 126 MHz when implemented in Xilinx 10.1i, Virtex-5 technology. the speed is quite appreciable when compared to other existing works. the implemented architecture meets the required rate for processing of HD-1080 format video sequence.
We target the problem of image Denoising using Gaussian Processes Regression (GPR). Being a non- parametric regression technique, GPR has received much attention in the recent past and here we further explore its vers...
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ISBN:
(纸本)9781467385640
We target the problem of image Denoising using Gaussian Processes Regression (GPR). Being a non- parametric regression technique, GPR has received much attention in the recent past and here we further explore its versatility by applying it to a denoising problem. the focus is primarily on the design of a local gradient sensitive kernel that captures pixel similarity in the context of image denoising. this novel kernel formulation is used to shape the smoothness of the joint GP prior. We apply the GPR denoising technique to small patches and then stitch back these patches, this allows the priors to be local and relevant, also this helps us in dealing with GPR complexity. We demonstrate that our GPR based technique gives better PSNR values in comparison to existing popular denoising techniques.
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