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Main problem frequently encountered in all schemes transform domain watermarking technique is the robustness and imperceptibility. Due to achieved optimal result most algorithms of image watermarking using combination two or more transformation domain. This paper proposed Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) to embed binary watermark to color Image. Before the message...
In this paper, we propose a pedestrian attribute recognition approach and a CNN-based person re-identification framework enhanced by pedestrian attributes. The knowledge of person attributes can help video surveillance tasks like person re-identification as well as person search, semantic video indexing and retrieval to overcome viewpoint changes with their robustness to the inherent visual appearance...
Although single-shot fringe projection profilometry (FPP) techniques are known to allow effective 3-dimensional measurements (3D) of moving objects, their robustness is often of concern particularly if the object has vivid textures on its surface. Besides, traditional approaches only focus on 3D measurements but ignore the need in many applications of mapping the 3D measurements to the 2-dimensional...
Persistent detection and tracking of moving vehicles in airborne imagery provide indispensable information for many traffic surveillance applications including traffic monitoring and management, navigation systems, activity recognition and event detection. This paper presents a collaborative Spatial Pyramid Context-aware detection and Tracking system (SPCT) for moving vehicles in dense urban aerial...
Currently, China has the fastest growing air transportation market in the world. Resilience to external events is critical to ensure an efficient and reliable transportation of passengers. This study investigates the robustness of the Chinese airline network under disruptions at their critical airports as well as the evolution of the networks' robustness from the year 2010 to 2015. Among the 24 Chinese...
At present, the effective tracking of pedestrians is still a challenging task due to factors such as illumination change, pose variation, motion blur and occlusion. In this paper, we propose a simple and effective tracking algorithm which exploits the spatio-temporal context. Based on a existing Bayesian framework, we take full advantage of the relevance of the region of interest to its local context,...
Random forest has emerged as a powerful classification technique with promising results in various vision tasks including image classification, pose estimation and object detection. However, current techniques have shown little improvements in visual tracking as they mostly rely on piece wise orthogonal hyperplanes to create decision nodes and lack a robust incremental learning mechanism that is much...
We propose a novel measure for template matching named Deformable Diversity Similarity – based on the diversity of feature matches between a target image window and the template. We rely on both local appearance and geometric information that jointly lead to a powerful approach for matching. Our key contribution is a similarity measure, that is robust to complex deformations, significant...
We present a novel, purely affinity-based natural image matting algorithm. Our method relies on carefully defined pixel-to-pixel connections that enable effective use of information available in the image and the trimap. We control the information flow from the known-opacity regions into the unknown region, as well as within the unknown region itself, by utilizing multiple definitions of pixel affinities...
We present a novel method to track 3D models in color and depth data. To this end, we introduce approximations that accelerate the state-of-the-art in region-based tracking by an order of magnitude while retaining similar accuracy. Furthermore, we show how the method can be made more robust in the presence of depth data and consequently formulate a new joint contour and ICP tracking energy. We present...
Nowadays, human has used computers and especially, its applications to manage and solve daily problems, such as fly booking, traffic control, detecting abnormal actions of vehicle, etc. Those tasks must be automatic, rapid and precise to adapt with real time, which may alert the local transportation or police officers as early as possible in hope of reducing risk or furthermore, fatal road accidents...
This paper presents a computational framework for accurately estimating the disparity map of plenoptic images. The proposed framework is based on the variational principle and provides intrinsic sub-pixel precision. The light-field motion tensor introduced in the framework allows us to combine advanced robust data terms as well as provides explicit treatments for different color channels. A warping...
In order to reduce the effects caused by complex environments and ambient light conditions, a fast, robust and effective obstacles detection method of vehicles based on image analysis of multi-feature is proposed. Firstly, regions of interest (ROI) which contain lanes, vehicles and few parts of interference background are extracted in the input image by detecting gradient feature in rows. Secondly,...
Currently, the only mass-market service robots are floor cleaners and lawn mowers. Although available for more than 20 years, they mostly lack intelligent functions from modern robot research. In particular, the obstacle detection and avoidance is typically a simple physical collision detection. In this work, we discuss a prototype autonomous lawn mower with camera-based non-contact obstacle avoidance...
It is critical to classify the landing terrain from aerial images when an unmanned aerial vehicle lands at an unprepared site autonomously by using a vision sensor. Owing to the interference of illumination variations and noises, different terrains may show a similar image feature and the same terrain may have a different image feature, which brings great difficulties to image classification. To address...
Text embedded in natural scene images provide rich semantic information about the scene, which is of great value for content-based image applications. Due to the variety of text appearance and the complexity of scene context, however, text detection in natural images remains a challenging task. In this paper, we propose a robust text detection method that hierarchically and progressively localizes...
In this paper, we present a novel framework to incorporate high-level guidance and low-level features to automatically identify salient objects based on two ideas. The first one considers the specific location prior to encode visual saliency, while the second one estimates image saliency using contrast with respect to background regions. The proposed framework consists of the following three steps:...
Fragment reconstruction aims to restore broken images and documents via matching spatial adjacent fragments. As the existing solutions in the literature still remain problematic, we present a novel feature descriptor, Normal Direction Local Binary Pattern (termed as ND-LBP), for document/image fragment matching. ND-LBP is based on the conventional LBP descriptor, however, it outstands LBP by introducing...
Scene-text detection in natural-scene images is an important technique because scene texts contain location information such as names of places and buildings, but many difficulties still remain regarding practical use. In this paper, we tackle two problems of scene-text detection. The first is the discontiguous component problem in specific languages that contain characters consisting of discontiguous...
Intelligent vehicles heavily rely on robust and accurate self-localization. Global navigation satellite systems (GNSS) are not reliable in urban environments due to multipath and shadowing effects. Vision-based localization offers a promising alternative. We present a high-precision six degrees of freedom self-localization method using multiple cameras covering the surrounding environment. First,...
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