Automatic Generation of Action Sequence Images from Burst Shots

Abstract

Many sports enthusiasts, from novice photographers to professional publishers, rely on manual image segmentation with tools like Photoshop to combine multiple images of a bike trick or basketball dunk into a single image by cutting out the foreground of each image and overlaying it onto the background of one image. The goal of this project is to develop an algorithm that can automatically combine multiple images generated from burst shots of an action into a single image that clearly shows the full action. This requires three main tasks for each set of images, including background alignment between images in the cases when the camera is moving (using feature detection and matching), segmentation of the foreground and background components of each image even in cases when portions of the background might be moving, and finally cleanly combining the foreground image segments all of the images onto a single background image. The algorithm described in this paper successfully compiles a variety of image sets, including those where the foreground object overlaps between images or sets with multiple objects, but fails to compile sets where multiple objects cross paths during the action.

Domain: Image Processing

Language: MATLAB

Contact Detail

Ph.no: 7200555526

e-mail: info.nanosoftwares@gmail.com

R3E: Reliable Reactive Routing Enhancement for Wireless Sensor Networks

Abstract

Providing reliable and efficient communication under fading channels is one of the major technical challenges in wireless sensor networks (WSNs), especially in industrial WSNs (IWSNs) with dynamic and harsh environments. In this work, we present the Reliable Reactive Routing Enhancement (R3E) to increase the resilience to link dynamics for WSNs/IWSNs. R3E is designed to enhance existing reactive routing protocolsto provide reliable and energy-efficient packet delivery against the unreliable wireless links by utilizing the local path diversity. Specifically, we introduce a biased back off scheme during the route-discovery phase to find a robust guide path, which can provide more cooperative forwarding opportunities. Along this guide path, data packets are greedily progressed toward the destination through nodes’ cooperation without utilizing the location information. Through extensive simulations, we demonstrate that compared to other protocols, R3E remarkably improves the packet delivery ratio, while maintaining high energy efficiency and low delivery latency.

Domain: Networking

Language: MATLAB

Contact Detail

Ph.no: 7200555526

e-mail: info.nanosoftwares@gmail.com

High Dynamic Range Image Compression by Optimizing Tone Mapped Image Quality Index

Abstract

Tone mapping operators (TMOs) aim to compress high dynamic range (HDR) images to low dynamic range (LDR) ones so as to visualize HDR images on standard displays. Most existing TMOs were demonstrated on specific examples without being thoroughly evaluated using well-designed and subject validated image quality assessment models. A recently proposed tone mapped image quality index (TMQI) made one of the first attempts on objective quality assessment of tone mapped images. Here, we propose a substantially different approach to design TMO. Instead of using any predefined systematic computational structure for tone mapping (such as analytic image transformations and/or explicit contrast/edge enhancement), we directly navigate in the space of all images, searching for the image that optimizes an improved TMQI. In particular, we first improve the two building blocks in TMQI—structural fidelity and statistical naturalness components—leading to a TMQI-II metric. We then propose an iterative algorithm that alternatively improves the structural fidelity and statistical naturalness of the resulting image. Numerical and subjective experiments demonstrate that the proposed algorithm consistently produces better quality tone mapped images even when the initial images of the iteration are created by the most competitive TMOs. Meanwhile, these results also validate the superiority of TMQI-II over TMQI.

Domain: Image Processing

Language: MATLAB

Contact Detail

Ph.no: 7200555526

e-mail: info.nanosoftwares@gmail.com

Swap-and-randomize: A Method for Building Low-latency HPC Interconnects

Abstract

Random network topologies have been proposed to create low-diameter, low-latency interconnection networks in large-scale computing systems. However, these topologies are difficult to deploy in practice, especially when re-designing existing systems, because they lead to increased total cable length and cable packaging complexity. In this work we propose a new method for creating random topologies without increasing cable length: randomly swap link endpoints in a non-random topology that is already deployed across several cabinets in a machine room. We quantitatively evaluate topologies created in this manner using both graph analysis and cycle-accurate network simulation, including comparisons with non-random topologies and previously-proposed random topologies.

Domain : Networking

Language : JAVA

Contact Detail

Ph.no : 7200555526

e-mail: info.nanosoftwares@gmail.com

A Resource-Constrained Asymmetric Redundancy Elimination Algorithm

Abstract

We focus on the problem of efficient communications over access networks with asymmetric bandwidth and capability. We propose a resource-constrained asymmetric redundancy elimination algorithm (RCARE) to leverage downlink bandwidth and receiver capability to accelerate the uplink data transfer. RCARE can be deployed on a client or a proxy. Different from existing asymmetric algorithms, RCARE uses a flexible matching mechanism to identify redundant data and allocates a small sender cache to absorb the high downlink traffic overhead. Compared to existing redundancy elimination algorithms, RCARE provides a scalable sender cache that is adaptive based on resource and performance. We evaluate RCARE with real traffic traces collected from multiple servers and a campus gateway. The trace-driven simulation results indicate that RCARE achieves higher goodput gains and reduces downlink traffic compared to existing asymmetric communication algorithms. We design an adaptation algorithm for resource-constrained senders sending multiple data streams. Our algorithm takes samples from data streams and predicts how to invest cache size on individual data streams to achieve maximal uplink goodput gain. The adaptation algorithm improves the goodput gain by up to 87% compared to the baseline. In first 10% of data streams (sorted by the optimal goodput gains), RCARE achieves up to 42% goodput gain on average.

Domain : Networking

Language : JAVA

Contact Detail

Ph.no : 7200555526

e-mail: info.nanosoftwares@gmail.com

A New Secure Image Transmission Technique via Secret-Fragment-Visible Mosaic Images by Nearly Reversible Color Transformations

Abstract

            A new secure image transmission technique is proposed, which transforms automatically a given large-volume secret image into a so-called secret-fragment-visible mosaic image of the same size. The mosaic image, which looks similar to an arbitrarily selected target image and may be used as a camouflage of the secret image, is yielded by dividing the secret image into fragments and transforming their color characteristics to be those of the corresponding blocks of the target image. Skillful techniques are designed to conduct the color transformation process so that the secret image may be recovered nearly losslessly. A scheme of handling the overflows/underflows in the converted pixels’ color values by recording the color differences in the untransformed color space is also proposed. The information required for recovering the secret image is embedded into the created mosaic image by a lossless data hiding scheme using a key. Good experimental results show the feasibility of the proposed method.

Domain : Image Processing

Contact Detail

Ph.no : 7200555526

e-mail: info.nanosoftwares@gmail.com

Robust Face Recognition from Multi-View Videos

Abstract

Multiview face recognition has become an active research area in the last few years. In this paper, we present an approach for video-based face recognition in camera networks. Our goal is to handle pose variations by exploiting the redundancy in the multiview video data. However, unlike traditional approaches that explicitly estimate the pose of the face, we propose a novel feature for robust face recognition in the presence of diffuse lighting and pose variations. The proposed feature is developed using the spherical harmonic representation of the face texture-mapped onto a sphere; the texture map itself is generated by back-projecting the multiview video data. Video plays an important role in this scenario. First, it provides an automatic and efficient way for feature extraction. Second, the data redundancy renders the recognition algorithm more robust. We measure the similarity between feature sets from different videos using the reproducing kernel Hilbert space. We demonstrate that the proposed approach outperforms traditional algorithms on a multiview video database.

Domain : Image Processing

Contact Detail

Ph.no : 7200555526

e-mail id : info.nanosoftwares@gmail.com