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The recent advancement of web-scale digital advertising saw a paradigm shift from the conventional focus of digital advertisement distribution towards integrating digital processes and methodologies and forming a seamless workflow of advertisement design, production, distribution, and effectiveness monitoring. In this work, we implemented a computational framework for the predictive analysis of the...
The use of autonomous drones in industrial inspection is gaining momentum with improvements in hardware and control. Considering the availability of historical data as drones gather information by regular sorties, a new opportunity for change detection is emerging for inspection and maintenance. In this paper, we propose a visual change detection framework using multi- scale super pixel approach....
Studies on visual attention of patients with Alzheimer's disease and dementia are a promising way for keeping track of an individual patients image recognition ability over time. This research seeks to expand upon the current applications of combining the Android operating system with TensorFlow by providing QA diagnostics alongside a visual question answering (VQA) platform for image analysis. This...
This paper describes the implementation of a 3D handheld scanning approach based on Kinect. User may get the 3D scans at a very fast rate using real time scanning devices like Kinect. These devices have been utilized in several applications, but the scanning lacks in the accuracy and reliability of the 3D data, which makes their employment a difficult task. This research proposed the 3D handheld scanning...
Measurement of visual quality is of significant importance to many image processing tasks. The target of image quality assessment (IQA) is to design effective computational models in order to automatically predict the quality of images in a perceptual consistent manner. We propose a full reference (FR) IQA metric based on information-theoretic IQA framework and passive aggressive learning algorithm...
This paper presents a fusion of monocular camera-based metric localization, IMU and odometry in dynamic environments of public roads. We build multiple vision-based maps and use them at the same time in localization phase. For the mapping phase, visual maps are built by employing ORB-SLAM and accurate metric positioning from LiDAR-based NDT scan matching. This external positioning is utilized to correct...
The popularly used subjective estimator- mean opinion score (MOS) is often biased by the testing environment, viewers mode, domain expertise, and many other factors that may actively influence on actual assessment. We therefore, devise a no- reference subjective quality assessment metric by exploiting the nature of human eye browsing on videos. The participants' eye-tracker recorded gaze-data indicate...
The intensive annotation cost and the rich but unlabeled data contained in videos motivate us to propose an unsupervised video-based person re-identification (re-ID) method. We start from two assumptions: 1) different video tracklets typically contain different persons, given that the tracklets are taken at distinct places or with long intervals; 2) within each tracklet, the frames are mostly of the...
Automatic image aesthetics rating has received a growing interest with the recent breakthrough in deep learning. Although many studies exist for learning a generic or universal aesthetics model, investigation of aesthetics models incorporating individual user’s preference is quite limited. We address this personalized aesthetics problem by showing that individual’s aesthetic preferences exhibit strong...
This paper presents a method for assess the risk index in a power transformers park, risk index is a metric that allows park administrator to ensure an optimal physical asset management, allocating properly financial and human resources in operation and maintenance actions. Assessing risk index requires calculating two secondary sub-index termed failure probability and consequence factor. Those indexes...
Direct method for visual odometry has gained popularity, it needs not to compute feature descriptor and uses the actual values of camera sensors directly. Hence, it is very fast. However, its accuracy and consistency are not satisfactory. Based on these considerations, we propose a tightly-coupled, optimization-based method to fuse inertial measurement unit (IMU) and visual measurement, in which uses...
This paper explores freehand physical interaction in egocentric Mixed Reality by performing a usability study on the use of hand posture estimation sensors. We report on precision, interactivity and usability metrics in a task-based user study, exploring the importance of additional visual cues when interacting. A total of 750 interactions were recorded from 30 participants performing 5 different...
Mobile phones equipped with a monocular camera and an inertial measurement unit (IMU) are ideal platforms for augmented reality (AR) applications, but the lack of direct metric distance measurement and the existence of aggressive motions pose significant challenges on the localization of the AR device. In this work, we propose a tightly-coupled, optimization-based, monocular visual-inertial state...
We report on the results of the first visual search and rating study (N60) evaluating human gaze when assessing the realism of image composites. The effects of object identity knowledge and mismatched feature type on observers' gaze and subjective realism scores are studied. Gaze metrics used include: fixation count, fixation duration, time and duration of first fixation on target object, as well...
This paper proposes a real-time Audio and Video Artifacts Detection Tool (AVADT), solution that wraps implemented artifacts detection methods for most important and common audio and video artifacts. It can also be used for evaluation of different modules and functions of device under testing (e.g. encoder, decoder). AVADT can operate in two modes: offline mode for evaluation of existing, locally stored...
While strong progress has been made in image captioning recently, machine and human captions are still quite distinct. This is primarily due to the deficiencies in the generated word distribution, vocabulary size, and strong bias in the generators towards frequent captions. Furthermore, humans – rightfully so – generate multiple, diverse captions, due to the inherent ambiguity in the captioning task...
To bridge the gap between humans and machines in image understanding and describing, we need further insight into how people describe a perceived scene. In this paper, we study the agreement between bottom-up saliency-based visual attention and object referrals in scene description constructs. We investigate the properties of human-written descriptions and machine-generated ones. We then propose a...
Camera-enabled sensors deployed for visual monitoring will cover a region of the target field, providing information for many innovative applications based on wireless sensing. Actually, some areas of the monitored field may have more relevance than others, according to the characteristics of the applications, which may indicate that such areas need better coverage to avoid blind spots and achieve...
In this paper, we propose a computational strategy to enhance the performance of Image Quality Metrics (IQM) by using content specific features of an image. We do this by creating Visual Error Importance (VEI) map that is applied to the error maps computed by the IQM. A global optimization can be used to compute the VEI map that is optimal for any given IQM. We demonstrate this concept by categorizing...
Spatial visualization (SV) skills contribute to success in engineering. However, ample research from American university settings indicates that various subsets of engineering students have significantly less-developed SV skills than those demonstrated by the majority male population. A multi-modal SV workshop intervention was provided within a first-year engineering projects design course in order...
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