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Object detection in a video is a challenging task in the field of image processing. Some applications of the domain are Human Machine Interaction (HMI), Security and Surveillance, Supplemented Authenticity, Traffic Monitoring on Roads, Medicinal Imaging etc. There happens to be a number of methods available for object detection. Each of the method has some constraints on the kind of application it...
Automated video analysis in fishery has drawn increasing attention since it is more scalable and deployable in conducting survey, such as fish catch tracking and size measurement, than traditional human observers. However, there are challenges from the wild sea environment, such as the rapid motion of the tide and the white water foam on the surface, which can create large noise in video data. In...
Visual saliency approaches aim to detect regions that attract human attention more than others. To find salient objects in a video shot we start from the hypothesis that moving objects attract attention more than other and are considered salient. In this paper, a novel video saliency model is proposed. Saliency map is the result of a combination between a dynamic map and a static map. For each pair...
Currently, many applications require following objects through a sequence of images. Typically, the motion is estimated by calculating the optical flow on monochrome images because it involves fewer computational cost. However, sometimes the intensity of the pixels may not be sufficient to successfully achieve the objective of identifying moving objects. In this paper, it is proposed to use models...
Leaf occlusion is a challenging issue in surveillance video particularly in public outdoor places. The objective of leaf occlusion detection is to automatically determine whether the video suffers from leaf occlusion or not. To tackle this challenge, this paper proposes a learning-based leaf occlusion detection approach, which incorporates a new feature map into a deep learning network. The proposed...
The demand for people tracking in dense crowds is increasing, but it is a challenging problem in the computer vision field. "Crowd tracking" is extremely difficult because of hard occlusions, various motions and posture changes. In particular, we need to handle occlusions for more robust tracking. This paper discusses robust crowd tracking based on a combination of supervoxels and optical...
Unmanned aerial vehicles (UAVs) are widely used for commercial and military purposes. UAVs are mostly dependent on an Inertial Measurement Unit(IMU) for navigation. We have presented an alternate approach to estimate the states of an UAV using only onboard camera which can be either used alone or assimilated with the IMU output to enable reliable, accurate and robust navigation. As UAVs are generally...
Multiview video is becoming increasingly popular as the format for 3D video systems that use autostereoscopic displays or freeviewpoint navigation capabilities. However, the algorithms that drive these applications are not yet mature and can suffer from subtle irregularities such as color imbalances inbetween different cameras. Regarding the problem of color correction, state-of-the-art methods directly...
Over the years Vision based real time gesture recognition system has witnessed an exponential growth because of its manifoldness applications, ranging from sign language to virtual reality and its ability to interact with system efficiently through HCI. In this paper, we have proposed a hand gesture recognition system for American Sign Language recognition using important features of hand such as...
In this paper we present a method for roadside vegetation detection intended for traffic safety and road infrastructure maintenance. While many published methods are using Near Infrared images which are suitable for vegetation detection, our method uses features from the visible spectrum allowing the use of a common color camera. The presented method uses a set of carefully selected color and texture...
In this paper we present a method for roadside vegetation detection from video obtained from a moving vehicle with intended use in road infrastructure maintenance and traffic safety. While many published methods are using Near Infrared images which are suitable for vegetation detection, our method uses image features from the visible spectrum allowing the use of a common color camera. The presented...
Optical Flow estimation is used to estimate displacement vectors for each pixels in two frames of a video. This displacement vector says how quickly a pixel is moving across the image and direction of movement of each pixel. According to the direction of movement, a color is assigned to each flow vector and intensity of color varies according to the magnitude of velocity. In this paper, optical flow...
Optical Flow is a very important topic in computer vision, with applications in object tracking, motion estimation and video compression. Recently, Tao et al. proposed the Simple-Flow algorithm - a non-iterative method whose running times increase sublinearly with the number of pixels. SimpleFlow does not use global optimization and uses only local evidence, achieving significant speedups in parallel...
Particle filter (PF) has proven successfully for nonlinear and non-Gaussian estimate problems, but its degeneracy will influence the results of tracking. Therefore in the paper, the optical flow algorithm is utilized to generate the proposal distribution of particle filter. With the velocity message which is estimated by optical flow algorithm, the particles could be generated in a right direction...
Although there are many works that have been done in face tracking, most of them are not suitable for realtime requirement in smart phones which have computation limitations. In the other hand, simple algorithms capable of applying for mobile devices still have some problems in tracking. With the combination approach, we propose a face tracking system that is fast, accuracy, and easy to implement...
Recently automatic video surveillance in the digital video recording CCTV system is rapidly becoming one of the most accepted security system. The dangerous situations such as forest fire, flood, and terrorism are increasing, and cause serious casualty and property loss. In this paper, we particularly focus on the fire detection system in video. The proposed block-based fire detection algorithm consists...
With rapid advancement in technology, numerous applications are required, such as for face and gesture recognition. However, various methods previous researchers have developed and presented suffer from limitations. Therefore, this study proposes an FPGA-based gesture recognition system by rewriting the largest computational complexity of optical flow to perform parallel processing architecture, and...
The paper proposes a novel method for estimating the optical flows from the sequentially captured images with using their own color information. The gradient method is well known as one of the conventional methods to estimate the flows, and then the spatial and temporal derivative of the images are used in the method. Since the color images have richer information than the monochrome ones, they should...
The interest in the production of stereoscopic contents is growing rapidly. High quality stereo material can be produced using vertical stereo camera rig but complex color discrepancies occur because of the optical characteristic of the half mirror. These discrepancies may severely increase an audience's sense of fatigue if s/he watches these stereoscopic contents for a long time. The color matching...
In this work we present a novel method for tracking an unknown number of objects with a single camera system in real-time. The proposed algorithm is based on high-accuracy optical flow and finite set statistics. In this framework the target state is treated as a random vector and the number of possible objects as a random number, which has to be estimated correctly. We are able to deal with false...
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