194 results for Klette, Reinhard

  • Concise Computer Vision: An Introduction into theory and algorithms

    Klette, Reinhard (2014)

    Book
    The University of Auckland Library

    Concise Computer Vision provides an accessible general introduction to the essential topics in computer vision, highlighting the role of important algorithms and mathematical concepts. Classroom-tested programming exercises and review questions are also supplied at the end of each chapter.

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  • Approximated Ground Truth for Stereo and Motion Analysis on Real-World Sequences (Poster)

    Liu, Zhifeng; Klette, Reinhard (2009)

    Conference poster
    The University of Auckland Library

    Conference details: The 3rd Pacific-Rim Symposium on Image and Video Technology (PSIVT2009) Tokyo, Japan, January 13th—16th, 2009 http://psivt2009.nii.ac.jp/ We approximate ground truth for real-world stereo sequences and demonstrate its use for the performance analysis of a few selected stereo matching and optic flow techniques. Basically we assume zero roll and constant tilt of an ego-vehicle (for about 10 seconds) driving on a planar road.

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  • Inclusion of a Second-Order Prior into Semi-Global Matching. (2009)

    Hermann, Simon; Klette, Reinhard; Destenfanis, Eduardo (2009)

    Conference poster
    The University of Auckland Library

    Conference details: The 3rd Pacific-Rim Symposium on Image and Video Technology (PSIVT2009) Tokyo, Japan, January 13th—16th, 2009 http://psivt2009.nii.ac.jp/ We consider different parameter settings for SGM, suggest to include a second order prior into the smoothness term of the energy function, and propose and test a new cost function. Some preprocessing (edge images) proves to be of value for improving SGM stereo results on real-world data.

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  • Recovery Rate of Clustering Algorithms. (2009)

    Li, Fajie; Klette, Reinhard (2009)

    Conference poster
    The University of Auckland Library

    Conference details: The 3rd Pacific-Rim Symposium on Image and Video Technology (PSIVT2009) Tokyo, Japan, January 13th—16th, 2009 http://psivt2009.nii.ac.jp/ We provide a simple and general way for defining the recovery rate of clustering algorithms using a given family of old clusters for evaluating the performance when calculating a family of new clusters. The recovery rate may be calculated by using an approximate and efficient algorithm.

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  • A Variant of Adaptive Mean Shift-Based Clustering

    Li, Fajie; Klette, Reinhard (2008)

    Conference poster
    The University of Auckland Library

    Conference Details: ICONIP 2008 - 15th International Conference on Neural Information. Processing of the Asia-Pacific Neural Network Assembly November 25-28, 2008, Auckland, New Zealand We are interested in clustering sets of highly overlapping clusters. For example, given is an observed set of stars (considered to be a set of points); how to find (recover) clusters which are the contributing galaxies of the observed union of those clusters? Below we propose a modification of an adaptive mean shift-based clustering algorithm (called Algorithm 1) proposed in 2003 by B. Geogescu, I. Shimsoni and P. Meer

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  • Landmark Initialization for Unscented Kalman Filter Sensor Fusion for Monocular Camera Localization

    Hartmann, G; Huang, F; Klette, Reinhard (2013-03)

    Journal article
    The University of Auckland Library

    The determination of the pose of the imaging camera is a fundamental problem in computer vision. In the monocular case, difficulties in determining the scene scale and the limitation to bearing-only measurements increase the difficulty in estimating camera pose accurately. Many mobile phones now contain inertial measurement devices, which may lend some aid to the task of determining camera pose. In this study, by means of simulation and real-world experimentation, we explore an approach to monocular camera localization that incorporates both observations of the environment and measurements from accelerometers and gyroscopes. The unscented Kalman filter was implemented for this task. Our main contribution is a novel approach to landmark initialization in a Kalman filter; we characterize the tolerance to noise that this approach allows.

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  • Goal: Real-Time Segmentation via Graph Cut Goal: Real-Time Segmentation via Graph Cut

    Vaudrey, Tobi; Wedel, Andreas; Rabe, Clemens; Klappstein, Jens; Klette, Reinhard (2008)

    Conference poster
    The University of Auckland Library

    Conference Details: 2008 23rd International Conference Image and Vision Computing New Zealand. IVCNZ 08. Lincoln University, Christchurch, 26-28 November 2008. http://www.lvl.co.nz/ivcnz2008/ The detection of moving objects is a crucial part of driver assistance systems. This paper tackles this issue using computer vision. Two approaches are investigated, monocular and stereoscopic. The base principals and implementational issues are discussed and detailed, high- lighting areas of concern. In both cases, the detection is based on motion analysis of individually tracked image points (optical ow). The monoc- ular approach relies solely on the optical ow, where as the stereoscopic approach also takes stereo depth information into account. In both ap- proaches the motion analysis provides a motion metric which corresponds to the likelihood that the tracked point is moving. Based on this metric the points are segmented into objects by employing the globally op- timal graph cut algorithm. These approaches are then compared and contrasted using real-world vehicle image sequences.

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  • An Approach for Evaluating Robustness of Edge Operators using Real-World Driving Scenes

    Al-Sarraf, Ali; Vaudrey, Tobi; Klette, Reinhard; Woo, Young Woon (2008)

    Conference poster
    The University of Auckland Library

    Conference Details: 2008 23rd International Conference Image and Vision Computing New Zealand Lincoln University, Christchurch, 26-28 November 2008. http://www.lvl.co.nz/ivcnz2008/ Over the past 20 years there have been many papers that compare and evaluate di erent edge operators. Most of them focus on accuracy and also do comparisons against synthetic data. This paper focuses on real-world driver assistance scenes and does a comparison based on robustness. The three edge operators compared are Sobel, Canny and the under-publicized phase-based Kovesi-Owens operator. The Kovesi- Owens operator has the distinct advantage that it uses one pre-selected set of parameters and can work across almost any type of scene, where as other operators require parameter tuning. The results from our comparison show that the Kovesi-Owens operator is the most robust of the three, and can get decent results, even under weak illumination and varying gradients in the images. Keywords: edge operators, edge robustness evaluation, Kovesi-Owens, phase operators

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  • Animated Non-Photorealistic Rendering in Multiple Styles

    Chen, T-Y; Klette, Reinhard (2013-11)

    Conference item
    The University of Auckland Library

    This paper presents an algorithm and its applications for artistic rendering of recorded video data following ideas of non-photorealistic rendering. The proposed algorithm does not only work on a variety of artistic rendering styles for static photography but it can also be applied to the creation of artistic videos. Cartoon-like and comic-like styles are the two artistic styles considered in this paper. For creating successfully an artistic video, three key challenges are addressed: temporal (or colour) consistency, stylistic flexibility, and scalability. Our work on addressing these challenges started with collecting samples of image and video data. Based on experimental results, we designed a method for video-based non-photorealistic rendering from those input data, either in cartoon-like or in comics-like style. The paper demonstrates the benefit of the designed video-based rendering framework by comparing its results with results obtained from existing Android apps.

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  • Inverse Skeletal Strokes

    Liu, D; Klette, Reinhard (2013-11)

    Conference item
    The University of Auckland Library

    The skeletal stroke method is a general brush tool which can take a straight vector artwork as “ink”. It is easy to apply, but it is limited by the requirement of straight inputs. To offer additional input options, we present inverse skeletal strokes, a method for straightening warped vector artworks. Our method takes a user stroke to help understanding the structure of an input artwork. The key-idea is finding a set of arcs which show the “directional trend” of the artwork, and map the artwork into a new version in which these arcs are straightened. We propose a measure representing the degree of parallelism between two arcs. Using this measure, we select a set of arcs from the input artwork which are approximately parallel to the given user stroke. This is a condensed representation of a user’s intention. Then we transform the user stroke with the goal to maximize the degree of parallelism to each of the selected approximately parallel arcs. At last, we parametrize the artwork with respect to the optimized stroke, and map it into a straight version.

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  • Accuracy of Trajectories Estimation in a Driver-Assistance Context

    Khan, W; Klette, Reinhard (2014)

    Conference item
    The University of Auckland Library

    Feature-point tracking for the purpose of object tracking in a driver-assistance context is not an easy task. First, to track rigid objects, feature points have to be matched frame-by-frame and then, by using disparity maps, their real-world position can be derived, from which the object velocity is estimated. Unfortunately, a feature-point matcher cannot find (reliable) matches in all frames. In fact, the performance of a matcher varies with the type of feature-point detector and descriptor used. Our comparison of different feature-point matchers gives a general impression of how descriptor performance degrades as a rigid object approaches the ego-vehicle in a collision-scenario video sequence. To handle the mismatches, we use a Kalman-filter-based tracker for each tracked feature point. The tracker with the maximum number of matches and with a most recent match is chosen as the optimal tracker. The role of the optimal tracker is to assist in updating the tracker of a feature point which had no match. The optimal tracker is also used in estimating the object velocity. To understand the behaviour of the safety system, we used the DoG detector in combination with SURF, BRIEF, and FREAK descriptors, while linBP and iSGM are used as stereo matchers. The novelty in our work is the performance evaluation of a stereo-based collision avoidance system (avoidance by brake warning) in a real collision scenario.

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  • Incremental Structured ICP Algorithm

    Geng, Haokun; Chien, J; Nicolescu, Radu; Klette, Reinhard (2014-12-08)

    Conference item
    The University of Auckland Library

    Variants of the ICP algorithm are widely used in many vision- based applications, such as visual odometry, structure from motion, 3D reconstruction, or object segmentation. Establishing correct correspon- dences between two sets of 3D points, generated by stereo vision, needs to take those uncertainties into account. We propose a novel variant of the traditional ICP algorithm for solving the mentioned alignment problem. Our method, named incremental structured iterative closest point, aims at improved registrations of 3D points calculated for real world data. Evaluations are carried out by measuring the distances between two in- puts, in both local and global perspectives, and experimental results are visually presented in this paper.

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  • Third-Eye Stereo Analysis Evaluation Enhanced by Data Measures

    Suaste, V; Caudillo, D; Shin, Bok Suk; Klette, Reinhard (2013-07)

    Conference item
    The University of Auckland Library

    Third-eye stereo analysis evaluation compares a virtual image, derived from results obtained by binocular stereo analysis, with a recorded image at the same pose. This technique is applied for evaluating stereo matchers on long (or continuous) stereo input sequences where no ground truth is available. The paper provides a critical and constructive discussion of this method. The paper also introduces data measures on input video sequences as an additional tool for analyzing issues of stereo matchers occurring for particular scenarios. The paper also reports on extensive experiments using two top-rated stereo matchers.

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  • Wrong roadway detection for multi-lane roads

    Tao, J; Shin, Bok Suk; Klette, Reinhard (2013)

    Conference item
    The University of Auckland Library

    The paper contributes to the detection of driving on the wrong side of the road by addressing in particular multi-lane road situations. We suggest a solution using video data of a single camera only for identifying the current lane of the ego-vehicle. GPS data are used for knowing defined constraints on driving directions for the current road.

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  • Feature extraction and classification for insect footprint recognition

    Shin, Bok Suk; Klette, Reinhard; Russell, James (2012)

    Conference item
    The University of Auckland Library

    We propose a method to extract and classify insect footprints for the purpose of recognition. Our four-level procedural feature extraction model is defined as follows: First, images produce new data via the trace transform. Second, for reducing the dimensionality of the produced data, we apply some mathematical conversions. Third, dimensionality-reduced data are converted into frequency components. Finally, characteristic signals with significant components of representative values are created by excluding insignificant factors such as those related to noise. For classification, based on uncertain features, we propose a decision method defined by fuzzy weights and a fuzzy weighted mean. The proposed fuzzy weight decision method estimates weights according to degrees of contribution. Weights are assigned by ranking the degree of a feature's contribution. We present experimental results of classification by using the proposed method on scanned insect footprints. Experiments show that the proposed method is suitable for noisy footprints with irregular directions, or symmetrical patterns in the extracted segments.

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  • Improved segmentation for footprint recognition of small mammals

    Shin, Bok Suk; Zheng, Y; Russell, James; Klette, Reinhard (2012)

    Conference item
    The University of Auckland Library

    In this paper we improve the automatic extraction of segments by resolving some of the issues for collected rat footprints, such as incomplete, fading, merged, or overlapping prints, or cuts due to the applied rectangular clipping process. First, binarization is by an adaptive method (proposed by Otsu) on the given input segment. Second, we remove small artefacts with a subsequent adaptive method. Third, merged regions are separated by a morphological method using an adaptive mask. Next, we find meaningful pads (central pad or toes) by analysing geometric relations defined by triangulation. Finally we reconstruct damaged footprints by using a convex-hull algorithm. We present experimental results of reconstructed footprints, and distributions of extracted features for improved segments. In the proposed technique, we automatically improve the quality and reliability of a scanned footprint image so as not to lose potential information for subsequent identification steps.

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  • Novel Backprojection Method for Monocular Head Pose Estimation

    Ju, K; Shin, Bok Suk; Klette, Reinhard (2013-07)

    Journal article
    The University of Auckland Library

    Estimating a driver???s head pose is an important task in driver-assistance systems because it can provide information about where a driver is looking, thereby giving useful cues about the status of the driver (i.e., paying proper attention, fatigued, etc.). This study proposes a system for estimating the head pose using monocular images, which includes a novel use of backprojection. The system can use a single image to estimate a driver???s head pose at a particular time stamp, or an image sequence to support the analysis of a driver???s status. Using our proposed system, we compared two previous pose estimation approaches. We introduced an approach for providing ground-truth reference data using a mannequin model. Our experimental results demonstrate that the proposed system provides relatively accurate estimations of the yaw, tilt, and roll angle. The results also show that one of the pose estimation approaches (perspective-n-point, PnP) provided a consistently better estimate compared to the other (pose from orthography and scaling with iterations, POSIT) using our proposed system.

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  • 3D Cascade of Classifiers for Open and Closed Eye Detection in Driver Distraction Monitoring

    Rezaei, Mahdi; Klette, Reinhard (2011)

    Conference item
    The University of Auckland Library

    Eye status detection and localization is a fundamental step for driver awareness detection. The efficiency of any learning-based object detection method highly depends on the training dataset as well as learning parameters. The research develops optimum values of Haar-training parameters to create a nested cascade of classifiers for real-time eye status detection. The detectors can detect eye-status of open, closed, or diverted not only from frontal faces but also for rotated or tilted head poses. We discuss the unique features of our robust training database that significantly influenced the detection performance. The system has been practically implemented and tested in real-world and real-time processing with satisfactory results on determining driver???s level of vigilance.

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  • A flexible method for localisation and classification of footprints of small species

    Geng, Haokun; Russell, James; Shin, Bok Suk; Nicolescu, Radu; Klette, Reinhard (2011)

    Conference item
    The University of Auckland Library

    In environmental surveillance, ecology experts use a standard tracking tunnel system to acquire tracks or footprints of small animals, so that they can measure the presence of any selected animals or detect threatened species based on the manual analysis of gathered tracks. Unfortunately, distinguishing morphologically similar species through analysing their footprints is extremely difficult, and even very experienced experts find it hard to provide reliable results on footprint identification. This expensive task also requires a great amount of efforts on observation. In recent years, image processing technology has become a model example for applying computer science technology to many other study areas or industries, in order to improve accuracy, productivity, and reliability. In this paper, we propose a method based on image processing technology, it firstly detects significant interest points from input tracking card images. Secondly, it filters irrelevant interest points in order to extract regions of interest. Thirdly, it gathers useful information of footprint geometric features, such as angles, areas, distance, and so on. These geometric features can be generally found in footprints of small species. Analysing the detected features statistically can certainly provide strong proof of footprint localization and classification results. We also present experimental results on extracted footprints by the proposed method. With appropriate developments or modifications, this method has great potential for applying automated identification to any species.

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  • Integrated Pedestrian and Direction Classification using a Random Decision Forest

    Tao, Junli; Klette, Reinhard (2013-12)

    Conference item
    The University of Auckland Library

    For analysing the behaviour of pedestrians in a scene, it is common practice that pedestrian localization, classification, and tracking are conducted consecutively. The direction of a pedestrian, being part of the pose, implies the future path. This paper proposes novel Random Decision Forests (RDFs) to simultaneously classify pedestrians and their directions, without adding an extra module for direction classification to the pedestrian classification module. The proposed algorithm is trained and tested on the TUD multi-view pedestrian and Daimler Mono Pedestrian Benchmark data-sets. The proposed integrated RDF classifiers perform comparable to pedestrian or direction trained separated RDF classifiers. The integrated RDFs yield results comparable to those of state-of-the-art and baseline methods aiming for pedestrian classification or body direction classification, respectively.

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