Pub Date : 2017-09-01DOI: 10.1109/ISPA.2017.8073561
T. Pribanić, T. Petković, M. Donlic, Tom Radman, J. Salvi
In the last several years 3D shape reconstruction and 3D registration using mobile platforms, i.e. smartphones and tablets, have been an increasingly active research avenue. Besides camera(s), nowadays mobile devices are equipped with a variety of sensors, including an accelerometer, a magnetometer and a gyroscope which are, among other applications, extensively used for the task of 3D registration too. To this end usually more than two sensors are utilized. In this work we demonstrate the usage of a tablet as 3D structured light scanner, and we further propose 3D registration method using only single sensor data, supplied by an accelerometer. Briefly, using an accelerometer our method first estimates only few candidate rotations in the spatial domain. Next, for each rotation candidate, the optimal translation is computed using a correlation function, efficiently implemented in the frequency domain. The final 3D registration parameters are chosen based on ICP refinement. The experimental results show a very close agreement with ground truth data. The proposed method is not restricted to mobile platforms only, but it is applicable to any 3D device which can be upgraded with an ubiquitous accelerometer.
{"title":"3D registration on mobile platforms using an accelerometer","authors":"T. Pribanić, T. Petković, M. Donlic, Tom Radman, J. Salvi","doi":"10.1109/ISPA.2017.8073561","DOIUrl":"https://doi.org/10.1109/ISPA.2017.8073561","url":null,"abstract":"In the last several years 3D shape reconstruction and 3D registration using mobile platforms, i.e. smartphones and tablets, have been an increasingly active research avenue. Besides camera(s), nowadays mobile devices are equipped with a variety of sensors, including an accelerometer, a magnetometer and a gyroscope which are, among other applications, extensively used for the task of 3D registration too. To this end usually more than two sensors are utilized. In this work we demonstrate the usage of a tablet as 3D structured light scanner, and we further propose 3D registration method using only single sensor data, supplied by an accelerometer. Briefly, using an accelerometer our method first estimates only few candidate rotations in the spatial domain. Next, for each rotation candidate, the optimal translation is computed using a correlation function, efficiently implemented in the frequency domain. The final 3D registration parameters are chosen based on ICP refinement. The experimental results show a very close agreement with ground truth data. The proposed method is not restricted to mobile platforms only, but it is applicable to any 3D device which can be upgraded with an ubiquitous accelerometer.","PeriodicalId":117602,"journal":{"name":"Proceedings of the 10th International Symposium on Image and Signal Processing and Analysis","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129492072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1109/ISPA.2017.8073586
Martin Soldic, Darijan Marcetic, Marijo Maracic, Darko Mihalić, S. Ribaric
The identified weaknesses of most of state-of-the-art trackers are inability to cope with long-term full occlusions, abrupt motion, detecting and tracking a reappeared target. In this paper, we present a robust real-time single face tracking system with several new key features: semi-automatic target tracking initialization based on a robust face detector, an effective target loss estimation based on a response of a position correlation filter, a candidate image patch selection for re-initialization supported with a short- and long-term memories (STM and LTM). These memories are used for tracking re-initialization during online learning procedure. The STM is used to select an image patch as candidate for re-tracking based on stored position correlation filters (from current frame) in case of short-term full occlusions, while the LTM stores aggregated position correlation filters (online learned) is used to recover the tracker from long-term full occlusions. Validation of the tracking system was performed by evaluation on a subset of videos from Online Tracking Benchmark (OTB) dataset and our own video.
{"title":"Real-time face tracking under long-term full occlusions","authors":"Martin Soldic, Darijan Marcetic, Marijo Maracic, Darko Mihalić, S. Ribaric","doi":"10.1109/ISPA.2017.8073586","DOIUrl":"https://doi.org/10.1109/ISPA.2017.8073586","url":null,"abstract":"The identified weaknesses of most of state-of-the-art trackers are inability to cope with long-term full occlusions, abrupt motion, detecting and tracking a reappeared target. In this paper, we present a robust real-time single face tracking system with several new key features: semi-automatic target tracking initialization based on a robust face detector, an effective target loss estimation based on a response of a position correlation filter, a candidate image patch selection for re-initialization supported with a short- and long-term memories (STM and LTM). These memories are used for tracking re-initialization during online learning procedure. The STM is used to select an image patch as candidate for re-tracking based on stored position correlation filters (from current frame) in case of short-term full occlusions, while the LTM stores aggregated position correlation filters (online learned) is used to recover the tracker from long-term full occlusions. Validation of the tracking system was performed by evaluation on a subset of videos from Online Tracking Benchmark (OTB) dataset and our own video.","PeriodicalId":117602,"journal":{"name":"Proceedings of the 10th International Symposium on Image and Signal Processing and Analysis","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124612986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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