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Visual odometry is the most suitable method for recovering the camera motion in the context of video processing applications. The main advantages it brings are the accuracy of the estimation, the computation efficiency, and the elimination of the need to synchronize a video processing system with other odometry sensors. There is a large amount of recently published visual odometry methods, but none...
Video annotation is a kind of "high-level feature extraction" or "semantic concept detection", which is a promising approach to bridging semantic gap between low-level features and user descriptions. In this paper we propose a two layer video annotation scheme based on video structure and the visual context information through the video clips. To improve the retrieval performance...
Many various mechanical systems such as robotic arms, conveyer drives, multimass systems contain flexible joints. Because of described feature these objects are vulnerable for oscillations. To reduce its occurrence input shaping method might be used. The algorithm of input shaping is very simple to use, provides good effects and doesn't require the changes in control loop. The algorithm's work is...
Therapy environments for robot-assisted stroke rehabilitation are mostly static, in that objects are earmarked for different functional tasks, object locations remain fixed, trajectories are predefined and tasks manually selected. This work advocates the need for a therapy environment that allows dynamic object positioning, different objects can be used for the same functional task and tasks can be...
An Image-based fixed wing Unmanned Aerial Vehicle (UAV) has autonomous flight control system which tracks targets to be pursued. This system is more prominent because it is based on visual sight around the aircraft to track the target. Targets will be identified as a feature in the image field captured by camera. By using the position of features in the image, a visual servoing algorithm is implemented...
The pupillary response has been used to measure mental workload because of its sensitivity to stimuli and high resolution. The goal of this study was to diagnose the cognitive effort involved with a task that was presented visually. A multinomial processing tree (MPT) was used as an analytical tool in order to disentangle and predict separate cognitive processes, with the resulting output being a...
In existing convolutional neural networks (CNNs), both convolution and pooling are locally performed for image regions separately, no contextual dependencies between different image regions have been taken into consideration. Such dependencies represent useful spatial structure information in images. Whereas recurrent neural networks (RNNs) are designed for learning contextual dependencies among sequential...
Identification of a human face in a crowded flux plays an important role in the context of surveillance. Considerable amount of research has been carried out on face identification in different applications. Accordingly, different researchers propose new algorithms. This paper attempts to showcase a novel methodology through which any face may be identified in a large crowd of human face. This proposed...
The interacting visual maps (IVM) algorithm introduced in [1] is able to perform the joint approximate inference of several visual quantities such as optic-flow, gray-level intensities and ego-motion, using a sparse input coming from a neuromorphic dynamic vision sensor (DVS). We show that features of the model such as the intrinsic parallelism and distributed nature of its computation make it a natural...
As the era of Moore's Law and increasing CPU clock rates nears its stopping point the focus of chip and hardware design has shifted to increasing the number of computation cores present on the chip. This increase can be most clearly seen in the rise of Graphic Processing Units (GPU) where hundreds or thousands of slower cores work in parallel to accomplish tasks. Programming for these chips represents...
The turtle retina is organized with predominantly two important classes of cells. The first, known as A cells, is sensitive only to light intensity. The other, known as B cells, is also sensitive to direction of targets. We propose models for both types of cells and demonstrate results the models yield. We also show the encoding properties of a single cells and show how a single B-cell can be used...
Microcircuits in the visual cortex of freshwater turtles have been revisited. These consist of a model of the retina, the lateral geniculate nucleus (LGN) and the visual cortex. In this paper, we present, via simulation how visual input on the retina is subsequently processed by the LGN leading up to an input to the cortex that generates a wave of activity. To gain access to the information content...
Automatic data classification is a computationally intensive task that presents variable precision and is considerably sensitive to the classifier configuration and to data representation, particularly for evolving data sets. Some of these issues can best be handled by methods that support users’ control over the classification steps. In this paper, we propose a visual data classification methodology...
Some visual saliency models have been proposed to describe how the human visual system perceives and processes visual information. In this paper we describe four frequency domain visual saliency models based on new spectrum processing methods. The four saliency models are the Gamma Corrected Spectrum (GCS) model, the Gamma Corrected Log Spectrum (GCLS) model, the Gaussian Filtered Spectrum (GFS) model,...
Visual attention is one of the most important mechanisms in the human visual perception. Recently, its modeling becomes a principal requirement for the optimization of the image processing systems. Numerous algorithms have already been designed for 2D saliency prediction. However, only few works can be found for 3D content. In this study, we propose a saliency model for stereoscopic 3D video. This...
Biological systems span several orders of magnitude in space and time from intracellular pathways to tissue-level processes. Many studies focus on molecular level events while other studies focus on cellular level and tissue level interactions. The immune system is highly complex and dynamic, encompassing hierarchical interactions with dimensions ranging from nanometers to meters and time scales from...
In this paper, we present a novel approach towards the integration of visual attention, object based attention and object recognition. Our system is scalable in regard to the required framerate or usage of computational power. Therefore, it is perfectly suited for robotic applications, where time is a crucial factor. We enhance and evaluate our previously presented visual attention system based on...
Usual attention is an important mechanism of the human visual system. It allows reducing the amount of information to be processed and accelerates the overall process of vision. Several models for images and videos have been proposed in the literature with encouraging results. However, most existing saliency models do not take into account the multimodal aspect of the video (audio and image). In this...
We introduce the web-based simulation and visualization tool Webdemo, designed for supplementing science, technology, engineering and mathematics (STEM) courses in higher education with interactive examples. The flexible simulation system supports a great variety of visualizations and mathematical operations. To ensure open access, the web front end does neither require additional software nor user...
Playing a vital role, saliency has been widely applied for various image analysis tasks, such as content-aware image retargeting, image retrieval and object detection. It is generally accepted that saliency detection can benefit from the integration of multiple visual features. However, most of the existing literatures fuse multiple features at saliency map level without considering cross-feature...
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