看得见的智能——人工智能在影视产业链中的应用和反思

影视业一贯以来将创意视为产业发展进步的核心所在,而人工智能时代的到来意味着技术的革新将重构影视产业原有的产业链和生态,给整个行业带来多方位的升级。本文从人工智能的起源、定义、赋能技术和应用出发,聚焦人工智能与影视产业结合所形成的智能影视产业链,对其结构布局和具体应用进行分析,最后做出思考和展望。

论影视创作中人工智能预测技术的应用

人工智能的发展为影视创作中智能预测技术的应用提供了可能性。人工智能预测技术能够为影视制作过程的前期准备提供决策建议,为内容创作提供优化方案,提高收视口碑,降低失败风险。在市场投放过程中,人工智能预测技术能够通过机器智能从海量数据中提取有价值的信息,构建并优化预测算法;通过认知智能获取受众观影时的神经数据,结合行为数据构建预测模型。同时,智能预测也需要关注隐私安全、教育审美、歧视偏见、商业控制等问题,以保持影视行业的健康发展。

基于多元智能理论的英语专业影视欣赏课作业设计与实践

作业是英语课程体系中不可缺少的重要组成部分,是完成教学任务、实现教学目标的重要环节,对学生知识的巩固和能力的培养起着举足轻重的作用。本文以多元智能理论为依托,结合任务教学,针对大学英语作业存在的问题,对英语专业影视欣赏课作业进行设计和实践研究。

Vehicle Real-time Location Based on Visual Perception Model

Vehicle recognition system (VRS) plays a very important role in the field of intelligent transportation systems.A novel and intuitive method is proposed for vehicle location.The method we provide for vehicle location is based on human visual perception model technique. The perception color space HSI in this algorithm is adopted.Three color components of a color image and more potential edge patterns are integrated for solving the feature extraction problem.A fast and automatic threshold technique based on human visual perception model is also developed.The vertical edge projection and horizontal edge projection are adopted for locating left-right boundary of vehicle and top-bottom boundary of vehicle, respectively. Very promising experimental results are obtained using real-time vehicle image sequences, which have confirmed that this proposed location vehicle method is efficient and reliable, and its calculation speed meets the needs of the VRS.