In this paper, we present a word extraction and recognition methodology from online cursive handwritten text-lines recorded by Leap motion controller The online text, drawn by 3D gesture in air, is distinct from usual...
详细信息
ISBN:
(纸本)9781479961016
In this paper, we present a word extraction and recognition methodology from online cursive handwritten text-lines recorded by Leap motion controller The online text, drawn by 3D gesture in air, is distinct from usual online pen-based strokes. The 3D gestures are recorded in air, hence they produce often non-uniform text style and jitter-effect while writing. Also, due to the constraint of writing in air, the pause of stroke-flow between words is missing. Instead all words and lines are connected by a continuous stroke. In this paper, we have used a simple but effective heuristic to segment words written in air. Here, we propose a segmentation methodology of continuous 3D strokes into text-lines and words. Separation of text lines is achieved by heuristically finding the large gap-information between end and start-positions of successive text lines. Word segmentation is characterized in our system as a two class problem. In the next phase, we have used Hidden Markov Model-based approach to recognize these segmented words. Our experimental validation with a large dataset consisting with 320 sentences reveals that the proposed heuristic based word segmentation algorithm performs with accuracy as high as 80.3%c and an accuracy of 77.6% has been recorded by HMM-based wordrecognition when these segmented words are fed to HMM. The results show that the framework is efficient even with cluttered gestures.
PatchMatch Stereo is a method generating a depth map from stereo images by repeatedly applying spatial propagation and view propagation to the depth map. The extension of PatchMatch Stereo for multi-view 3D reconstruc...
详细信息
ISBN:
(纸本)9781479961016
PatchMatch Stereo is a method generating a depth map from stereo images by repeatedly applying spatial propagation and view propagation to the depth map. The extension of PatchMatch Stereo for multi-view 3D reconstruction has been recently proposed. This extension is very ad hoc and does not fully utilize the potential of multi-view images, since the method generates a 3D point cloud by combining a set of depth maps obtained from each binocular stereo image pair. This paper proposes a multi-view 3D reconstruction method using PatchMatch Stereo. To fully utilize the impact of multi-view images, the proposed method have two key ideas: (i) integrate matching scores from multiple stereo image pairs and (ii) perform view propagation among multi-view images. The use of multi-view images makes it possible to generate a reliable depth map by reducing occlusions. Through a set of experiments, we demonstrate that the proposed method generates more reliable depth map from multi-view images than the conventional method.
The 3rd iapr asian conference on pattern recognition(acpr2015),sponsored by the International Association of patternrecognition(iapr)and supported by the Malaysian Image Analysis and Machine Intelligence Association(...
详细信息
The 3rd iapr asian conference on pattern recognition(acpr2015),sponsored by the International Association of patternrecognition(iapr)and supported by the Malaysian Image Analysis and Machine Intelligence Association(MIAMI)and IEEE Computational Intelligence Society(CIS)Malaysia Chapter will be held on November 3-6,2015,Kuala Lumpur,*** First asianconference on patternrecognition(acpr2011)was held at Beijing,China;while the second series(acpr2013)was held at Okinawa,Japan.
暂无评论