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Crowd analysis using cameras has attracted much attention for public safety and marketing. Among techniques of the crowd analysis, we focus on spatial people density estimation which estimates the number of people for each small area in a floor region. However, spatial people density cannot be estimated accurately for an area far from the camera because of the occlusion by people in a closer area...
Person re-identification is a challenging problem in multi-camera surveillance systems. Most current methods always aim at learning a global distance metric to overcome the visual appearance changes between images from different cameras. However, the feature variations between images are not constant over the entire feature space, thus one global metric is not always applicable to all feature variation...
The ability to automatically determine the road type from sensor data is of great significance for automatic annotation of routes and autonomous navigation of robots and vehicles. In this paper, we present a novel algorithm for content-based road type classification from images. The proposed method learns discriminative features from training data in an unsupervised manner, thus not requiring domain-specific...
Although multi-view datasets have become more accessible in the real-world applications, most state-of-the-art action recognition methods applied to those datasets rely on simple view agreement when combining local information from various views together. This leads to deteriorated performance in situations with view insufficiency and view disagreements. In this paper, we propose a novel framework...
Glint features have important roles in gaze tracking systems. But when the operation range of a gaze tracking system is enlarged, the performance of glint-feature-based (GFB) approaches will be degraded mainly due to the curvature variation problem at around the edge of the cornea. Although the pupil contour feature may provide complementary information to help estimating the eye gaze, existing methods...
In this paper, we propose a novel method of calibrating non-overlapping RGB-D cameras using one chessboard fixed with a laser pointer. A laser pointer is fixed at one calibration board so that its pose at the coordinate system of the calibration board can be obtained easily. While one of the RGB-D cameras observes the calibration board fixed with the laser pointer, the laser pointer project a spot...
This paper addresses the problem of silhouette-based human action segmentation and recognition in monocular sequences. Motion History Images (MHIs), used as 2D templates, capture motion information by encoding where and when motion occurred in the images. Inspired by codebook approaches for object and scene categorization, we first construct a codebook of temporal motion templates by clustering all...
In this paper, a novel method of the 2D Euclidean structure recovery in one view from the projections of N parallel conics is proposed. Without considering the conic dual to the absolute points (CDAP), we transform conic features from the homogeneous coordinates to the lifted coordinates. In the lifted space, the conic features have the similar properties to the point or line features, which especially...
The goal of this paper is to identify individuals by analyzing their gait. Instead of using binary silhouettes as input data (as done in many previous works) we propose and evaluate the use of motion descriptors based on densely sampled short-term trajectories. We take advantage of state-of-the-art people detectors to define custom spatial configurations of the descriptors around the target person...
Temporal artifacts due to sequential acquisition of measurements in compressed sensing manifest differently from a conventional optical camera. We propose a framework for dynamic scenes to estimate the relative global motion between camera and scene from measurements acquired using a compressed sensing camera. We follow an adaptive block approach where the resolution of the estimated motion path depends...
As vehicles travel through a scene, changes in aspect ratio and appearance as observed from a camera (or an array of cameras) make vehicle detection a difficult computer vision problem. Rather than relying solely on appearance cues, we propose a framework for detecting vehicles and eliminating false positives by utilizing the motion cues in the scene in addition to the appearance cues. As a case study,...
At the current rate of technological advancement and social acceptance thereof, it will not be long before wearable devices will be common that constantly record the field of view of the user. We introduce a new database of image sequences, taken with a first person view camera, of realistic, everyday scenes. As a distinguishing feature, we manually transcribed the scene text of each image. This way,...
This paper demonstrates a system for automatic detection of visual attention and identification of salient items at exhibitions (e.g. museum or an auction). The method is offline and is done on a video captured by a head mounted camera. Towards the estimation of attention, we define the notions of "saliency" and "interestingness" for an exhibition items. Our method is a combination...
The progress in fields science, information technology and communication have allowed, since the 1970s, developing new electronic aids for the blind in order to overcome the difficulties that the dog and cane do not respond. Among the systems of electronic substitution, are the sensory substitution systems that capture a low-resolution picture of the visual scene and transforming them into an another...
This paper demonstrates several improvements on implementing a fast monocular visual slam system (MonoSLAM) to navigate indoor aerial vehicle. These improvements include designing for the framework of the navigation system, redesigning of landmark patch matching method and giving new rules updating the image patch to overcome some particularly bad situation when landmarks are insufficient. We demonstrate...
In this paper, a vision based navigation method for autonomous landing of UAV is presented. First, the pose estimation based on the PnP problem solution is introduced. Because of the pixel position error in image, the estimation errors exist and the position errors are concussive while UAV approaches an airport, which is disadvantageous to the guidance and control for autonomous landing of UAV. Then,...
Multi-spectral images capture more information about a scene as compared to RGB images and have various scientific applications. But the high resolution multi-spectral cameras are very expensive which limits their wide applicability as compared to normal digital RGB cameras. In this paper a multi-spectral filter array design is proposed to capture multiple bands using the single-sensor architecture...
Person re-identification is a challenging problem in computer vision due to large variations of appearance among different cameras. Recently, metric learning is widely used to model the transformation between cameras. However, traditional metric learning based methods only learn one metric for the whole feature space, which cannot model different kinds of appearance variations well. In this paper,...
Human identification is very important for many applications. Most existing methods are based on ID cards or biometrical methods, such as fingerprint hard information or clothing color soft biometric trait. In this work, we propose a novel framework for human identification through recognizing human moving trajectory by two modalities, that is, the motion information from bird's eye view depth cameras...
This paper addresses the camera identification based on very low bit rate videos with time varying overall noise pattern statistics. First, the overall noise pattern of each frame of the videos is resized to a column vector. It is found that the elements of the resized vectors approximately follow the Laplace distribution. Hence, the second, the fourth and the sixth order statistic moments of each...
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