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This research proposes a convolutional neural network based pupil center detection method from an eye image which is captured by a wearable eye camera. This paper investigates the detection accuracy by applying several preprocessing, such as edge detection, and binarization. We find the preprocess method in order to speed up the computation time. We collected approximately 8,000 eye images with six...
Numerous image matching methods for wide range of applications have been invented in the last decade. When high precision and reliability of the object space point coordinates is highly demanding, a stereo image matching method which can produce conjugate point of images and a standard deviation of the matched point is examined. In this approach, image gradients are used locally to seek a conjugate...
We propose a novel method for inferring the state transition from bystander to participant in free-style conversational interactions, using physical behaviors acquired from cameras and a microphone. Although existing methods address participants and a presenter, these methods do not consider bystanders, who play an important role in the interaction. In the research field of cognitive science, the...
Appearance based multi-object tracking (MOT) is a challenging task, specially in complex scenes where objects have similar appearance or are occluded by background or other objects. Such factors motivate researchers to propose effective trackers which should satisfy real-time processing and object trajectory recovery criteria. In order to handle both mentioned requirements, we propose a robust online...
A free viewpoint application has been developed that yields an immersive user experience. The free viewpoint approach called the "billboard methodis" suitable for displaying a synthesized 3D view in a mobile device, but it suffers from the limitation that a billboard cannot present an accurate impression of depth for a foreground object, and it gives users an unacceptable impression from...
With the increasing use of unmanned aerial vehicles (UAVs) by consumers, automatic UAV detection systems have become increasingly important for security services. In such a system, video imagery is a core modality for the detection task, because it can cover large areas and is very cost-effective to acquire. Many detection systems consist of two parts: flying object detection and subsequent object...
Traffic Surveillance System (TSS) plays an important role in extracting necessary information (count, type, speed, etc.). In the area of Traffic Surveillance System (TSS), vehicle detection has emerged as an influential field of study. So far there has been a considerable amount of research to accommodate this subject. However, these studies almost address problems in developed countries where the...
The choice of motion models is vital in applications like image/video stitching and video stabilization. Conventional methods explored different approaches ranging from simple global parametric models to complex per-pixel optical flow. Mesh-based warping methods achieve a good balance between computational complexity and model flexibility. However, they typically require high quality feature correspondences...
Images are formed by counting how many photons traveling from a given set of directions hit an image sensor during a given time interval. When photons are few and far in between, the concept of image breaks down and it is best to consider directly the flow of photons. Computer vision in this regime, which we call scotopic, is radically different from the classical image-based paradigm in that visual...
Generalization performance of trained computer vision (CV) systems that use computer graphics (CG) generated data is not yet effective due to the concept of domain-shift between virtual and real data. Although simulated data augmented with a few real-world samples has been shown to mitigate domain shift and improve transferability of trained models, guiding or bootstrapping the virtual data generation...
We present a novel strategy to shrink and constrain a 3D model, represented as a smooth spline-like surface, within the visual hull of an object observed from one or multiple views. This new background or silhouette term combines the efficiency of previous approaches based on an image-plane distance transform with the accuracy of formulations based on raycasting or ray potentials. The overall formulation...
Machine learning techniques, namely convolutional neural networks (CNN) and regression forests, have recently shown great promise in performing 6-DoF localization of monocular images. However, in most cases image-sequences, rather only single images, are readily available. To this extent, none of the proposed learning-based approaches exploit the valuable constraint of temporal smoothness, often leading...
Localizing a query image against a 3D model at large scale is a hard problem, since 2D-3D matches become more and more ambiguous as the model size increases. This creates a need for pose estimation strategies that can handle very low inlier ratios. In this paper, we draw new insights on the geometric information available from the 2D-3D matching process. As modern descriptors are not invariant against...
Time-of-flight (TOF) depth cameras provide robust depth inference at low power requirements in a wide variety of consumer and industrial applications. These cameras reconstruct a single depth frame from a given set of infrared (IR) frames captured over a very short exposure period. Operating in this mode the camera essentially forgets all information previously captured - and performs depth inference...
In this work, we propose a novel way of efficiently localizing a sports field from a single broadcast image of the game. Related work in this area relies on manually annotating a few key frames and extending the localization to similar images, or installing fixed specialized cameras in the stadium from which the layout of the field can be obtained. In contrast, we formulate this problem as a branch...
Removing pixel-wise heterogeneous motion blur is challenging due to the ill-posed nature of the problem. The predominant solution is to estimate the blur kernel by adding a prior, but extensive literature on the subject indicates the difficulty in identifying a prior which is suitably informative, and general. Rather than imposing a prior based on theory, we propose instead to learn one from the data...
This paper tackles the photometric stereo problem in the presence of inaccurate lighting, obtained either by calibration or by an uncalibrated photometric stereo method. Based on a precise modeling of noise and outliers, a robust variational approach is introduced. It explicitly accounts for self-shadows, and enforces robustness to cast-shadows and specularities by resorting to redescending M-estimators...
This paper describes the use of Unmanned Aerial Vehicle (UAV) technology to fight apple scab. Specifically, it shows how it is possible to improve the scab risk evaluation basing on the actual apple leaves development status, yielded from UAV images, as input to the infection model. For this purpose, we introduce a new index, called Leaf Development Index (LDI), which is evaluated during the main...
Automatic detection of moving targets is one of important research area in the remote sensing field. In this paper, we propose a method that accurately detects moving targets in aerial videos using hierarchical spatiotemporal saliency analysis. First, coarse motion regions are extracted by utilizing global temporal saliency analysis. Based on these local candidate regions, spatial saliency methods...
A new radiometry and design framework has been introduced in the latest Digital Imaging and Remote Sensing Image Generation model (DIRSIG5) that allows for faster simulations while streamlining the generation of high-fidelity radiometric data. The same framework that allows for improved computational performance has also modularized simulation components to allow for extensive interchangeability based...
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