In this paper we present a software module for object recognition before robotic gripping with an anthropomorphic gripper. To this effect, recognizing the shape of an object using digital image processing algorithms, falling in the area... more
Machine Learning (ML) techniques have emerged as a viable option for X-ray screening. Fracture detection is a significant part of muscular X-ray image test. Automatic fracture detection for patients in distant regions helps paramedics in... more
Scale Invariant Feature Transform (SIFT) proposed by Lowe has been widely and successfully applied to object detection and recognition. However, the representation ability of SIFT features in face recognition has rarely been investigated... more
The article describes the research of image analysis methods. The methods of indexing images for the search of duplicate images, as well as methods for finding similar images based on the definition of key points are described. The... more
Despite broad investigation in content-based image retrieval (CBIR), issue to lessen the semantic gap between high-level semantics and local attributes of the image is still an important issue. The local attributes of an image such as... more
This paper presents a robust outlier elimination approach for multimodal retina image registration application. Our proposed scheme is based on the Scale-Invariant Feature Transform (SIFT) feature extraction and Partial Intensity... more
Monitoring and identification are vitally important to insect biodiversity conservation and protection. As a popular and comparatively well known order, Lepidoptera (moths and butterflies) are good indicators of insect biodiversity.... more
In this work, a novel approach for the automated transfer of Bounding Box (BB) and mask labels across different channels on multilens cameras is presented. For that purpose, the proposed method combines the well-known phase correlation... more
Mammographic breast density refers to the prevalence of fibroglandular tissue as it appears on a mammogram. Breast density is not only an important risk for developing breast cancer but can also mask abnormalities. Breast density... more
Scale-invariant feature transform (SIFT) is succeed in such a way that it become very easy to extensively employ image local feature in different computers vision and image processing software's. SIFT is very helpful to develop... more
Emerging mobile applications, such as augmented reality, demand robust feature detection at high frame rates. We present an implementation of the popular Scale-Invariant Feature Transform (SIFT) feature detection algorithm that... more
Real-world videos often contain dynamic backgrounds and evolving people activities, especially for those web videos generated by users in unconstrained scenarios. This paper proposes a new visual representation, namely scene aligned... more
Real-world videos often contain dynamic backgrounds and evolving people activities, especially for those web videos generated by users in unconstrained scenarios. This paper proposes a new visual representation, namely scene aligned... more
Real-world videos often contain dynamic backgrounds and evolving people activities, especially for those web videos generated by users in unconstrained scenarios. This paper proposes a new visual representation, namely scene aligned... more
Real-world videos often contain dynamic backgrounds and evolving people activities, especially for those web videos generated by users in unconstrained scenarios. This paper proposes a new visual representation, namely scene aligned... more
is still an open hard problem because of the semantic gap between low-level features and high-level features, largeness of database, keyframe's content, choosing feature.In this study we introduce a new approach for this problem based on... more
This paper presents an algorithm for video super-resolution based on scale-invariant feature transform (SIFT) matching. SIFT features are known to be a robust method for locating keypoints. The matching of these keypoints from different... more
Most popular hand-crafted key-point detectors such as Harris corner, SIFT, SURF aim to detect corners, blobs, junctions or other human defined structures in images. Though being robust with some geometric transformations, unintended... more
We present an Online Random Ferns (ORFs) classifier that progressively learns and builds enhanced models of object appearances. During the learning process, we allow the human intervention to assist the classifier and discard false... more
This paper describes an approach for mobile robot localization using a visual word based place recognition approach. In our approach we exploit the benefits of a stereo camera system for place recognition. Visual words computed from SIFT... more
Real-world camera networks are often characterized by very wide baselines covering a wide range of viewpoints. We describe a method not only calibrating each camera sequence added to the system automatically, but also taking advantage of... more
Human Activity Recognition (HAR) is a crucial component of computer vision, with applications in human-computer interaction and surveillance. As the need for HAR technology keeps increasing, so does the desire for solutions that can help... more
The construction of a high-resolution panoramic image from a sequence of input overlapping images of the same scene is called image stitching/mosaic. It is considered as an important, challenging topic in computer vision, multimedia, and... more
We present a method for solving two minimal problems for relative camera pose estimation from three views, which are based on three view correspondences of (i) three points and one line and the novel case of (ii) three points and two... more
This paper reports a novel algorithm for bootstrapping the automatic registration of unstructured 3D point clouds collected using co-registered 3D lidar and omnidirectional camera imagery. Here, we exploit the co-registration of the 3D... more
This paper presents a new approach for the automatic license plate recognition, which includes the SIFT algorithm in step to locate the plate in the input image. In this new approach, besides the comparison of the features obtained with... more
We present a novel algorithm, Compact Kd-Trees (Com-pactKdt), that achieves state-of-the-art performance in searching large scale object image collections. The algorithm uses an order of magnitude less storage and computations by making... more
We introduce and compare two algorithms related to ego-motion, applicable to a robot using a panoramic visual sensor in an unknown environment. The first method, computationally cheap, extends a family of bio-inspired navigation systems... more
For robots navigating using only a camera, illumination changes in indoor environments can cause re-localization failures during autonomous navigation. In this paper, we present a multisession visual SLAM approach to create a map made of... more
For robots navigating using only a camera, illumination changes in indoor environments can cause re-localization failures during autonomous navigation. In this paper, we present a multi-session visual SLAM approach to create a map made of... more
The hand vein pattern as a biometric trait for identification has attracted increasing interests in recent years thanks to its properties of uniqueness, permanence, non-invasiveness as well as strong immunity against forgery. In this... more
Recent investigations on human vision discover that the retinal image is a landscape or a geometric surface, consisting of features such as ridges and summits. However, most of existing popular local image descriptors in the literature,... more
Facial expression recognition is to determine the emotional state of the face regardless of its identity. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition.... more
Visual content description is a key issue for machine-based image analysis and understanding. A good visual descriptor should be both discriminative and computationally efficient while possessing some properties of robustness to viewpoint... more
The text associated with images provides valuable semantic meanings about image content that can hardly be described by low-level visual features. In this paper, we propose a novel multimodal approach to automatically predict the visual... more
Coins square measure integral a part of our day to day life. We tend to use coins everyplace like grocery market, banks, buses, trains etc. Therefore it is a basic want that coin is recognized and counted. The target of this paper is to... more
Highlights A novel method for text-independent writer identification. Organization of training samples for Convolutional Neural Network. Feature aggregation to form global features from local features. 99.97% accuracy to classify... more
Statistical characterization of morphological changes of dendritic spines is becoming of crucial interest in the field of neurobiology. Automatic detection and segmentation of dendritic spines promises significant reductions on the time... more
C ¸ürüklü and other members of the VPALAB for helping me to tackle the problems I had during this thesis. Special thanks to Tugba Karagöz for all the encouragement and support she has provided throughout the thesis.
![All the tracking algorithms, either reviewed or proposed in this thesis are differential methods that can only estimate the pose change between consecutive frames. In order to obtain the pose of the head at a given time ¢ relative to the first frame. pose differences between adjacent frames need to be accumulated. However since each pose change measurement is noisy, the accumulation of these measurements becomes noisier with time, potentially resulting in an unbounded drift. [2] All the tracking algorithms, either reviewed or proposed in this thesis are differential](https://figures.academia-assets.com/121098112/figure_010.jpg)
![Table 5.2: Performance results of the trackers over synthetic video sequences For testing the performance of our tracker we have used a hardware based tracker, Polhemus Fastrak [37] as the ground truth. The tracker consists of 3 parts: System Electronics Unit (SEU), a transmitter, and a receiver. SEU contains the hard- ware necessary to generate and sense the magnetic fields, compute position and orientation, and interface with the host computer via a RS-232 or a USB interface. The transmitter contains electromagnetic coils and is responsible for emitting the magnetic fields. The transmitter is the system’s reference frame for receiver mea- surements. The receiver unit contains the magnetic coils that detect the magnetic field emitted by the transmitter. Polhemus is a 3D motion tracker with 6 degrees of freedom. The tracker has an accuracy of 0.076cm RMS with 0.0005 cm resolution for the position and an accuracy 0.15° RMS with an 0.025° resolution for the ori- entation. In a laboratory environment with computers and metal furniture around, we observed lower accuracy than the specifications. However, the ground truth captured was still visually good enough to evaluate the head tracking algorithms considered in the thesis.](https://figures.academia-assets.com/121098112/table_002.jpg)
Image alignment is an essential task in many applications of hyperspectral remote sensing images. Before any processing, the images must be registered. The Maximally Stable Extremal Regions (MSER) is a feature detection algorithm that... more
Image registration is a common operation in any type of image processing, specially in remote sensing images. Since the publication of the scale-invariant feature transform (SIFT) method, several algorithms based on feature detection have... more
It is always a dream to recreate the experience of a particular place, the Panorama Virtual Reality has been interpreted as a kind of technology to create virtual environments and the ability to maneuver angle for and select the path of... more
The automatic detection of bilateral symmetry is a challenging task in computer vision and pattern recognition. This paper presents an approach for the detection of bilateral symmetry in digital single object images. Our method relies on... more
The development of picture editing software over the past several years has led to the establishment of a topic of active research in the field of digital image fraud detection. Passive forgery detection, or Copy Move Forgery Detection... more
Many people adopt cosmetic or medical changes for aesthetic or therapeutic objectives. The paper proposes a human identification technique for differentiating between samples taken before and after surgery. The system operates in three... more
Numerous scale-invariant feature matching algorithms using scale-space analysis have been proposed for use with perspective cameras, where scale-space is defined as convolution with a Gaussian. The contribution of this work is a method... more