N. Ancona, G. Creanza, D. Fiore, R. Tangorra, B. Dierickx, G. Meynants, D. Scheffer
{"title":"用于运动估计和碰撞时间检测的实时、小型化光学传感器","authors":"N. Ancona, G. Creanza, D. Fiore, R. Tangorra, B. Dierickx, G. Meynants, D. Scheffer","doi":"10.1117/12.262544","DOIUrl":null,"url":null,"abstract":"The paper presents a low cost, miniature sensor that is able to compute in real time (up to 1000 frames/sec) motion parameters like the degree of translation, expansion or rotation that is present in the observed scene, as well as the so-called time-to-crash (TTC), that is the time required for a moving object to collide with the sensor. The sensing principle is that of computing and analyzing the optical flow projected by the scene on the sensor focal plane, through a novel algorithmic technique, based on sparse sampling of the image and one-dimensional correlation. The hardware implementation of the algorithm is based on two custom VLSI chips: one is a CMOS image sensor, having nonstandard pixel geometry, while the other one is a digital correlator that computes at high speed the optical flow vectors. The high-level control and communication tasks are managed by a microcontroller, thus guaranteeing a high level of flexibility and adaptability of the sensor properties towards different application requirements and/or variable external conditions.","PeriodicalId":127521,"journal":{"name":"Advanced Imaging and Network Technologies","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Real-time, miniaturized optical sensor for motion estimation and time-to-crash detection\",\"authors\":\"N. Ancona, G. Creanza, D. Fiore, R. Tangorra, B. Dierickx, G. Meynants, D. Scheffer\",\"doi\":\"10.1117/12.262544\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a low cost, miniature sensor that is able to compute in real time (up to 1000 frames/sec) motion parameters like the degree of translation, expansion or rotation that is present in the observed scene, as well as the so-called time-to-crash (TTC), that is the time required for a moving object to collide with the sensor. The sensing principle is that of computing and analyzing the optical flow projected by the scene on the sensor focal plane, through a novel algorithmic technique, based on sparse sampling of the image and one-dimensional correlation. The hardware implementation of the algorithm is based on two custom VLSI chips: one is a CMOS image sensor, having nonstandard pixel geometry, while the other one is a digital correlator that computes at high speed the optical flow vectors. The high-level control and communication tasks are managed by a microcontroller, thus guaranteeing a high level of flexibility and adaptability of the sensor properties towards different application requirements and/or variable external conditions.\",\"PeriodicalId\":127521,\"journal\":{\"name\":\"Advanced Imaging and Network Technologies\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Imaging and Network Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.262544\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Imaging and Network Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.262544","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time, miniaturized optical sensor for motion estimation and time-to-crash detection
The paper presents a low cost, miniature sensor that is able to compute in real time (up to 1000 frames/sec) motion parameters like the degree of translation, expansion or rotation that is present in the observed scene, as well as the so-called time-to-crash (TTC), that is the time required for a moving object to collide with the sensor. The sensing principle is that of computing and analyzing the optical flow projected by the scene on the sensor focal plane, through a novel algorithmic technique, based on sparse sampling of the image and one-dimensional correlation. The hardware implementation of the algorithm is based on two custom VLSI chips: one is a CMOS image sensor, having nonstandard pixel geometry, while the other one is a digital correlator that computes at high speed the optical flow vectors. The high-level control and communication tasks are managed by a microcontroller, thus guaranteeing a high level of flexibility and adaptability of the sensor properties towards different application requirements and/or variable external conditions.