Browsing by Subject "Nearest neighbors"

Now showing 1 - 4 of 4

Open Access
3D human pose search using oriented cylinders
(IEEE, 2009-09-10) Pehlivan, Selen; Duygulu, Pınar
In this study, we present a representation based on a new 3D search technique for volumetric human poses which is then used to recognize actions in three dimensional video sequences. We generate a set of cylinder like 3D kernels in various sizes and orientations. These kernels are searched over 3D volumes to find high response regions. The distribution of these responses are then used to represent a 3D pose. We use the proposed representation for (i) pose retrieval using Nearest Neighbor (NN) based classification and Support Vector Machine (SVM) based classification methods, and for (ii) action recognition on a set of actions using Dynamic Time Warping (DTW) and Hidden Markov Model (HMM) based classification methods. Evaluations on IXMAS dataset supports the effectiveness of such a robust pose representation. ©2009 IEEE.
Open Access
Diversity based Relevance Feedback for Time Series Search
(2013) Eravci, B.; Ferhatosmanoglu H.
We propose a diversity based relevance feedback approach for time series data to improve the accuracy of search results. We first develop the concept of relevance feedback for time series based on dual-tree complex wavelet (CWT) and SAX based approaches. We aim to enhance the search quality by incorporating diversity in the results presented to the user for feedback. We then propose a method which utilizes the representation type as part of the feedback, as opposed to a human choosing based on a preprocessing or training phase. The proposed methods utilize a weighting to handle the relevance feedback of important properties for both single and multiple representation cases. Our experiments on a large variety of time series data sets show that the proposed diversity based relevance feedback improves the retrieval performance. Results confirm that representation feedback incorporates item diversity implicitly and achieves good performance even when using simple nearest neighbor as the retrieval method. To the best of our knowledge, this is the first study on diversification of time series search to improve retrieval accuracy and representation feedback. © 2013 VLDB Endowment.
Open Access
Hareket geçmişi görüntüsü yöntemi ile Türkçe işaret dilini tanima uygulaması
(IEEE, 2016-05) Yalçınkaya, Özge; Atvar, A.; Duygulu, P.
İşitme ve konuşma engelli bireylerin toplum içerisinde diger bireylerle sağlıklı şekilde iletişim kurabilmeleri açısından işaret dili çok önemli bir role sahiptir. Ne yazık ki işaret dilinin toplumda sadece duyarlı insanlar tarafından bilindiği ve bu sayının da azlıgı dikkat çekmektedir. Yaptığımız çalışma kapsamındaki amaç, geliştirdiğimiz sistem sayesinde işitme veya konuşma engeli mevcut olan bireylerin diğer bireylerle olan iletişiminde iyileşme sağlamaktır. Bu amaç doğrultusunda kameradan alınan işaret diline ait hareket bilgisi tanınabilmekte ve o hareketin ne anlama geldiği daha önceden eğitilen işaret diline ait hareket bilgileri ile karşılaştırılarak bulunabilmektedir. Hareket bilgilerinin kameradan alınan görüntülerden çıkarılması aşamasında "Hareket Geçmişi Görüntüsü" yöntemi kullanılmıştır. Bu bağlamdaki sınıflandırma işlemi için de "En Yakın Komşuluk" algoritması kullanılmıştır. Sonuç olarak geliştirilen sistem, eğitim kümesini kullanarak işaret dili hareketi için bir metin tahmin etmektedir. Toplamdaki sınıflandırma başarısı %95 olarak hesaplanmıştır.
Open Access
Multi-population parallel genetic algorithm using a new genetic representation for the euclidean traveling salesman problem
(İstanbul Technical University, 2005) Kapanoğlu, M.; Koç, İ. O.; Kara, İ.; Aktürk, Mehmet Selim
This paper introduces a multi-population genetic algorithm (M-PPGA) using a new genetic representation, the kth-nearest neighbor representation, for Euclidean Traveling Salesman Problems. The proposed M-PPGA runs M greedy genetic algorithms on M separate populations, each with two new operators, intersection repairing and cheapest insert. The M-PPGA finds optimal or near optimal solutions by using a novel communication operator among individually converged populations. The algorithm generates high quality building blocks within each population; then, combines these blocks to build the optimal or near optimal solutions by means of the communication operator. The proposed M-PPGA outperforms the GAs that we know of as competitive with respect to running times and solution quality, over the considered test problems including the Turkey81.