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We present a detailed study of Naive Bayes Nearest Neighbor (NBNN) proposed by Boiman et al., with application to scene categorization and video event detection. Our study indicates that using Dense-SIFT along with dimensionality reduction using PCA enables NBNN to obtain state-of-the-art results. We demonstrate this on two tasks: (1) scene image categorization on the UIUC 8 Sports Events Image Dataset...
In this paper, we propose an estimation algorithm for spatially-variant blur due to camera motion. To estimate the most accurate latent image, we integrated depth sensor (Microsoft Kinect) and IMU sensor with the camera. The joint analysis of the blurry image, IMU data and the depth data provide better recovery of the real camera motion during the course of the exposure. The reconstructed camera trajectory...
In this paper we propose a new data fitting method which, similar to RANSAC, fits data to a model using sample and consensus. The application of interest is fitting 3D point clouds to a prior geometric model. Where the RANSAC process uses random samples of points in the fitting trials, we propose a novel method which directs the sampling by ordering the points according to their contribution to the...
As a multi-billion dollar industry, scallop fisheries world-wide rely on maintaining healthy off-shore populations. Recent developments in the collection of optical images from extended areas of the ocean floor has opened the possibility of assessing scallop populations from imagery. The shear volume of data — upwards of 20,000 images per hour — implies that automatic image analysis is necessary....
Camera spectral sensitivity functions relate scene radiance with captured RGB triplets. They are important for many computer vision tasks that use color information, such as multispectral imaging, color rendering, and color constancy. In this paper, we aim to explore the space of spectral sensitivity functions for digital color cameras. After collecting a database of 28 cameras covering a variety...
The paper focuses on 3D structure and motion factorization from uncalibrated image sequences. A rank-4 affine factorization algorithm and a robust structure and motion factorization scheme are proposed to handle outlying and missing data. The novelty and main contribution of the paper are as follows: (i) The rank-4 factorization algorithm is a new addition to previous affine factorization family using...
We present an algorithm that uses a low resolution 3D sensor for robust face recognition under challenging conditions. A preprocessing algorithm is proposed which exploits the facial symmetry at the 3D point cloud level to obtain a canonical frontal view, shape and texture, of the faces irrespective of their initial pose. This algorithm also fills holes and smooths the noisy depth data produced by...
Conventional methods of gait analysis for person identification use features extracted from a sequence of camera images taken during one or more gait cycles. An implicit assumption is made that the walking direction does not change. However, cameras deployed in real-world environments (and often placed at corners) capture images of humans who walk on paths that, for a variety of reasons, such as turning...
This paper presents a wildfire smoke detection method based on a spatiotemporal bag-of-features (BoF) and a random forest classifier. First, candidate blocks are detected using key-frame differences and non-parametric color models to reduce the computation time. Subsequently, spatiotemporal three-dimensional (3D) volumes are built by combining the candidate blocks in the current key-frame and the...
The outreach of computer vision to non-traditional areas has enormous potential to enable new ways of solving real world problems. One such problem is how to incorporate technology in the effort to protect endangered and threatened species in the wild. This paper presents a snapshot of our interdisciplinary team's ongoing work in the Mojave Desert to build vision tools for field biologists to study...
We consider the problem of estimating the current satellite cloud map from a collection of broadly distributed, ground-based webcams. The approach uses historical, geo-referenced satellite imagery to learn a mapping between the satellite image and the ground imagery. We explore representational choices for inferring the cloud status based on the ground-level imagery and consider several alternatives...
We present a low cost markerless system for the optimization of athlete performance in sports such as pole vault, jumping and javelin throw. The system uses a number of calibrated cameras to capture a video of an athlete from different viewpoints. The athlete's body is then segmented from the background in each video frame. The silhouettes of the segmented body are then reprojected to reconstruct...
We present HotSpotter, a fast, accurate algorithm for identifying individual animals against a labeled database. It is not species specific and has been applied to Grevy's and plains zebras, giraffes, leopards, and lionfish. We describe two approaches, both based on extracting and matching keypoints or “hotspots”. The first tests each new query image sequentially against each database image, generating...
Secure Computation of Face Identification (SCiFI) [20] is a recently developed secure face recognition system that ensures the list of faces it can identify (e.g., a terrorist watch list) remains private. In this work, we study the consequences of malformed input attacks on the system — from both a security and computer vision standpoint. In particular, we present 1) a cryptographic attack that allows...
Human identification based on iris biometrics requires high resolution iris images of a cooperative subject. Such images cannot be obtained in non-intrusive applications such as surveillance. However, the full region around the eye, known as the periocular region, can be acquired non-intrusively and used as a biometric. In this paper we investigate the use of periocular region for person identification...
As iris recognition systems have been deployed in many security areas, liveness detection that can distinguish between real iris patterns and fake ones becomes an important module. Most existing algorithms focus on the appearance difference between real and fake iris (for example, printed patterns, cosmetic contact lenses etc.) which is a very difficult problem. Instead of studying image properties...
Many applications use multiple cameras to simultaneously capture imagery of a scene from a rigid, moving camera system over time. Multiple cameras often provide unique viewing angles but also additional levels of detail of a scene at different spatio-temporal resolutions. However, in order to benefit from this added information the sources must often be temporally aligned. As a result of cost and...
Large scale, class imbalanced data classification is a challenging task that occurs frequently in several computer vision tasks such as web video retrieval. A number of algorithms have been proposed in literature that approach this problem from different perspectives (e.g. Sampling, Cost-sensitive learning, Active learning). The challenge is two fold in this task — first the data imbalance causes...
In a lipreading system, lip extraction is a fundamental method that directly affects the final speech recognition results. However, most existing systems need to detect some facial features as prior-knowledge to construct the initial contour, and any erroneous feature detection will lead to an incorrect lip extraction. In order to solve this problem, this paper presents a new framework which integrates...
We address the problem of appearance-based person re-identification, which has been drawing an increasing amount of attention in computer vision. It is a very challenging task since the visual appearance of a person can change dramatically due to different backgrounds, camera characteristics, lighting conditions, view-points, and human poses. Among the recent studies on person re-id, color information...
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