難易度に応じた早期終了でBag-of-Words画像検索を高速化し見た目ベース自己位置推定に応用
Stopping Rules for Bag-of-Words Image Search and Its Application in Appearance-Based Localization
画像検索の難しさを見積もり、簡単なクエリでは計算を途中で打ち切る停止規則を導入してBoW検索の計算コストを大幅に削減し、見た目ベースの自己位置推定で有効性を示した論文。
著者: Kiana Hajebi, Hong Zhang
分類: cs.CV, cs.RO
原文アブストラクト
We propose a technique to improve the search efficiency of the bag-of-words (BoW) method for image retrieval. We introduce a notion of difficulty for the image matching problems and propose methods that reduce the amount of computations required for the feature vector-quantization task in BoW by exploiting the fact that easier queries need less computational resources. Measuring the difficulty of a query and stopping the search accordingly is formulated as a stopping problem. We introduce stopping rules that terminate the image search depending on the difficulty of each query, thereby significantly reducing the computational cost. Our experimental results show the effectiveness of our approach when it is applied to appearance-based localization problem.
