MP4技术：ISO媒体文件格式规范

ISO/IEC
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"ISO Media File format specification MP4 Technology under consideration for ISO/IEC 14496-1:2001/Amd 3" 本文档是关于ISO/IEC JTC1/SC29/WG11，即国际标准化组织/国际电工委员会下属的运动图像专家组(MPEG-4 Systems)的工作文件，详细阐述了ISO Media File Format，特别是针对ISO/IEC 14496-1:2001标准第三修正案（Amendment 3）中的MP4技术规范。 MP4（MPEG-4 Part 14）是一种用于存储数字媒体的容器格式，它允许组合多种数据流，如音频、视频、字幕和交互式内容。这个文件格式的规范旨在促进不同系统之间的多媒体内容交换，并支持多种应用场景。 文档的章节结构如下： 0.1 Base Format 这部分介绍了MP4文件的基础格式，包括文件的基本构成和其兼容性。 0.2 Usage - Interchange: 描述了MP4格式在不同系统和设备间进行多媒体数据交换的用途。 - Content Creation: 关注于内容创作者如何利用MP4格式来创作多媒体作品。 - Preparation for streaming: 阐述了MP4文件如何被优化以适应流式传输。 - Local presentation: 提供了MP4文件在本地播放时的处理方式。 - Streamed presentation: 讨论了MP4在实时流媒体环境中的应用。 0.3 Design principles 这一部分详细阐述了设计MP4格式时遵循的基本原则，这些原则确保了格式的灵活性、可扩展性和高效性。 0.4 Definitions 提供了与MP4文件格式相关的术语和定义，以便读者理解和应用规范。 1 Scope 明确了文档覆盖的范围，包括MP4格式的主要功能和目标。 2 Normative references 列出了规范制定所依据的标准参考文献。 3 Additional references 提供了对理解MP4格式有帮助的额外参考资料。 4 Streaming Support 讨论了MP4格式如何支持流媒体服务，包括： - Handling of Streaming Protocols: 介绍了MP4如何处理各种流媒体协议。 - Protocol ‘hint’ tracks: 解释了如何在MP4文件中添加“提示”轨道以支持流传输。 - Hint Track Format: 描述了提示轨道的具体格式。 5 File organization 深入探讨了MP4文件的组织结构： - Presentation structure: 包括文件结构、对象结构、元数据和媒体数据以及轨道标识。 - Meta-data Structure (Objects): 关注于元数据对象的结构和组成。 文档的其余部分可能继续详细说明文件结构的其他方面，如时间同步、数据类型、编码规则等，以确保MP4文件能在不同环境中正确解析和播放。MP4格式的设计不仅考虑了多媒体内容的存储，还考虑了网络传输、存储效率和未来技术的扩展性，使其成为当今广泛使用的多媒体容器格式之一。

QuickTime/MOV/Mp4 File Format Spec

2017-10-27 上传
This document, which supersedes the previous QuickTime File Format Specification, June, 2000, describes the format and content of QuickTime files

ISO/IEC 14496-1

2014-11-12 上传
ISO/IEC 14496-1 Second edition 2001-10-01 AMENDMENT 8 2004-10-01

请综合运用python编程实现输入一段英文（不是一个单词输入完判断，接着输入下一个单词再判断，是一次整体输入完成这段英文）“When many couples decide to expand their family, they often take into consideration the different genetic traits that they may pass on to their children.”，实现自动统计单词词频。程序运行时显示“请输入英文段落：”，结果要求不区分单词里任何字母大小写，只认单词即When 与when是一个单词

2023-06-01 上传
好的，下面是代码实现： ```python def word_count(text): # 将所有字符转换为小写 text = text.lower() ...consideration 1 the 2 different 1 genetic 1 traits 1 that 1 may 1 pass 1 on 1 children 1 ```

你的csgo账号被误封了，请你写一封英文申诉信

2023-03-28 上传
Dear Sir/Madam, I am writing to appeal a ban that was mistakenly placed on my Counter-Strike: Global Offensive account....Thank you for your time and consideration. Sincerely, [Your Name]

Third-party cookie will be blocked. Learn more in the Issues tab.这个问题怎么解决

2024-03-18 上传
3. Consent management platforms: Implementing a consent management platform allows websites to obtain user consent for data collection and tracking. By obtaining explicit consent, websites can ...

AV1 VVC HEVC difference

2023-03-31 上传
The AV1, VVC, and HEVC are video compression standards used for encoding and decoding video content. Here are the differences between them: 1. Compression efficiency: AV1 and VVC are newer ...

## Problem 7: Is BST Write a function `is_bst`, which takes a Tree `t` and returns `True` if, and only if, `t` is a valid binary search tree, which means that: - Each node has at most two children (a leaf is automatically a valid binary search tree). - The children are valid binary search trees. - For every node, the entries in that node's left child are less than or equal to the label of the node. - For every node, the entries in that node's right child are greater than the label of the node. An example of a BST is: ![bst](pic/bst.png) Note that, if a node has only one child, that child could be considered either the left or right child. You should take this into consideration. Hint: It may be helpful to write helper functions `bst_min` and `bst_max` that return the minimum and maximum, respectively, of a Tree if it is a valid binary search tree. ```python def is_bst(t): """Returns True if the Tree t has the structure of a valid BST. >>> t1 = Tree(6, [Tree(2, [Tree(1), Tree(4)]), Tree(7, [Tree(7), Tree(8)])]) >>> is_bst(t1) True >>> t2 = Tree(8, [Tree(2, [Tree(9), Tree(1)]), Tree(3, [Tree(6)]), Tree(5)]) >>> is_bst(t2) False >>> t3 = Tree(6, [Tree(2, [Tree(4), Tree(1)]), Tree(7, [Tree(7), Tree(8)])]) >>> is_bst(t3) False >>> t4 = Tree(1, [Tree(2, [Tree(3, [Tree(4)])])]) >>> is_bst(t4) True >>> t5 = Tree(1, [Tree(0, [Tree(-1, [Tree(-2)])])]) >>> is_bst(t5) True >>> t6 = Tree(1, [Tree(4, [Tree(2, [Tree(3)])])]) >>> is_bst(t6) True >>> t7 = Tree(2, [Tree(1, [Tree(5)]), Tree(4)]) >>> is_bst(t7) False """ "*** YOUR CODE HERE ***" ``` 。

2023-06-03 上传
>>> t2 = Tree(8, [Tree(2, [Tree(9), Tree(1)]), Tree(3, [Tree(6)]), Tree(5)]) >>> is_bst(t2) False >>> t3 = Tree(6, [Tree(2, [Tree(4), Tree(1)]), Tree(7, [Tree(7), Tree(8)])]) >>> is_bst(t3) ...

写一段Java实现Input In the first line you are given the number n of billionaires (1 ≤ n ≤ 10000). The following n lines contain information about these people: their names, cities where they were staying at the beginning of the period, and their fortunes. In the next line you are given the number m of days in the period for which you have the information (1 ≤ m ≤ 50000) and the number k of travels of the billionaires (0 ≤ k ≤ 50000). The following k lines contain the list of travels in the following format: the number of the day (from 1 to m−1), the name of the person, and the city of destination. You may assume that billionaires depart late at night and arrive to the destination city on the next day's morning. They cannot make more than one travel each day. The numbers of days in the list are not decreasing. All names of people and cities consist of at most 20 English letters; you must take into consideration the case of the symbols. The fortunes are in the range from 1 to 100 billions (one billion is a thousand million). Output In each line of the output give the name of a city and, after a space, the number of days during which this city was the first with respect to the sum of fortunes of the billionaires staying there. Leave out those cities for which there were no such days. The cities must be sorted alphabetically (with the usual symbol order: ABC...Zabc...z).

2023-05-30 上传
for (int i = day + 1; i ; i++) { long futureWealth = wealthByDay.getOrDefault(i, 0L); if (futureWealth > wealth) { break; } if (i - day > maxDays) { maxDays = i - day; } } } if (maxDays > 0...

Multiple object tracking (MOT) is a crucial task in computer vision, with a wide range of trackingalgorithms. Tracking and its complexity level depends on several factors, such as type of parameters beingtracked namely size, contour, position, velocity, and acceleration. It may also depend on number ofparameters used for tracking and the amount of prior knowledge about the target object. During trackingdifferent situations may arise such as, tracking of mobile object appearing for the first time in the scene.When representations of the object under consideration are available, it is feasible to learn it for the first time.Object tracking is an act of seeking for objects in successive frames of a video stream after learning has beencompleted. Even after so much research, MOT remains a difficult work since the object’s appearance canradically vary due to deformation, rotation out of plane, or changes in lighting conditions. Problem becomesmore challenging when tracking is to be done in dense places that consists of movable and immovable objects.

2023-06-06 上传
多目标跟踪(MOT)是计算机视觉中的一个关键任务，具有广泛的跟踪算法。跟踪及其复杂性水平取决于几个因素，例如被跟踪的参数类型，包括大小、轮廓、位置、速度和加速度。它还可能取决于用于跟踪的参数数量以及关于...

Please revise the paper：Accurate determination of bathymetric data in the shallow water zone over time and space is of increasing significance for navigation safety, monitoring of sea-level uplift, coastal areas management, and marine transportation. Satellite-derived bathymetry (SDB) is widely accepted as an effective alternative to conventional acoustics measurements over coastal areas with high spatial and temporal resolution combined with extensive repetitive coverage. Numerous empirical SDB approaches in previous works are unsuitable for precision bathymetry mapping in various scenarios, owing to the assumption of homogeneous bottom over the whole region, as well as the limitations of constructing global mapping relationships between water depth and blue-green reflectance takes no account of various confounding factors of radiance attenuation such as turbidity. To address the assumption failure of uniform bottom conditions and imperfect consideration of influence factors on the performance of the SDB model, this work proposes a bottom-type adaptive-based SDB approach (BA-SDB) to obtain accurate depth estimation over different sediments. The bottom type can be adaptively segmented by clustering based on bottom reflectance. For each sediment category, a PSO-LightGBM algorithm for depth derivation considering multiple influencing factors is driven to adaptively select the optimal influence factors and model parameters simultaneously. Water turbidity features beyond the traditional impact factors are incorporated in these regression models. Compared with log-ratio, multi-band and classical machine learning methods, the new approach produced the most accurate results with RMSE value is 0.85 m, in terms of different sediments and water depths combined with in-situ observations of airborne laser bathymetry and multi-beam echo sounder.

2023-02-18 上传
回答：本文提出了一种基于底部类型自适应的卫星深度测量（BA-SDB）方法，以解决传统卫星深度测量模型中假设底部均匀的局限性以及不能充分考虑影响反射率的干扰因素，如浊度等。通过基于聚类的底部反射率自适应分割，...
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